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  • MPI Ethno. Forsch.  (48)
  • HU Berlin
  • MARKK
  • Packt Publishing,  (48)
  • Python (Computer program language)  (48)
  • 1
    Online Resource
    Online Resource
    The complete LangChain & LLMs guide (2024)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781835885925 , 1835885926
    Language: English
    Pages: 1 online resource (1 video file (8 hr., 44 min.)) , sound, color.
    Edition: [First edition].
    DDC: 004.6
    Keywords: Artificial intelligence ; Computer programming ; Chatbots ; Application program interfaces (Computer software) ; Python (Computer program language) ; Intelligence artificielle ; Programmation (Informatique) ; Interfaces de programmation d'applications ; Python (Langage de programmation) ; artificial intelligence ; computer programming ; APIs (interfaces) ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: This comprehensive masterclass takes you on a transformative journey into the realm of LangChain and Large Language Models, equipping you with the skills to build autonomous AI tools. Starting with the basics, you'll set up your development environment, including OpenAI API and Python, and progress to advanced topics like LangChain's architecture, prompt templates, and parsers. The course meticulously guides you through creating complex chains, memory models, and agents, culminating in the development of practical applications such as PDF extractors, newsletter generators, and multi-document chatbots. With hands-on tutorials, you'll learn to leverage LangChain for tasks ranging from document loading and splitting to embedding vector stores for semantic similarity searches. By the end, you'll have the knowledge to implement AI in creative and impactful ways, from image-to-text conversion to building interactive chatbots and more, all while navigating the ethical considerations of AI deployment. What you will learn Configure OpenAI API and Python for AI development Create and manipulate LangChain prompt templates and parsers Implement LangChain memory models and chains for complex AI applications Develop real-world applications, including newsletter generators and chatbots Work with LangChain embeddings and vector stores for semantic searches Navigate the ethical and copyright implications of AI-generated content Audience This course is designed for a broad audience interested in artificial intelligence, from data scientists enhancing projects with AI and LangChain, to product managers boosting user experience with AI features. AI enthusiasts, tech innovators, and programmers will deepen their understanding of LangChain, unlocking new opportunities in AI-driven development and pioneering next-gen solutions. While specific knowledge of Python is not necessary, familiarity with programming concepts is essential. About the Author Paulo Dichone: Paulo Dichone, a seasoned software engineer and AWS Cloud Practitioner, is renowned for his expertise in Android, Flutter, and AWS, as well as being a best-selling instructor. Paulo has successfully imparted his knowledge to over 200,000 students across 175 countries, specializing in mobile app development for Android and iOS, web development, and AWS Cloud. His teaching philosophy centers on empowering students to excel as developers and AWS cloud practitioners, regardless of their prior experience. Beyond his professional pursuits, Paulo is devoted to his family, enjoys playing the guitar and mandolin, and loves to travel. He is committed to guiding students to achieve their highest potential in the tech industry.
    Note: Online resource; title from title details screen (O'Reilly, viewed March 4, 2024)
    URL: lizenzpflichtig
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    Online Resource
    MPI Ethno. Forsch.
  • 2
    Online Resource
    Online Resource
    Official next Js tutorial code along : React web development (2024)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781835463444 , 1835463444
    Language: English
    Pages: 1 online resource (1 video file (10 hr., 14 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.7/6
    Keywords: Web site development Computer programs ; Application software Development ; Python (Computer program language) ; Sites Web ; Systèmes-auteur ; Logiciels d'application ; Développement ; Python (Langage de programmation) ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: Next.js is a popular open-source JavaScript framework designed to make web development with React efficient and scalable. Next.js adds layers of abstraction to React and simplifies the process of building modern web applications. It provides a set of conventions and features that enhance the development experience, making it easier to create performant and SEO-friendly applications. This comprehensive Next.js course unfolds by beginning with an introduction to web development fundamentals, as it progresses through React basics, advanced Next.js concepts, and real-world deployment strategies. We will explore key topics such as server-side rendering (SSR), client-side rendering (CSR), static site generation (SSG), and incremental static regeneration (ISR). The course offers hands-on experience with a final project, covering everything from structuring applications to optimizing for performance and SEO. The modular format accommodates varying skill levels, ensuring a well-rounded and practical learning experience for all learners. Upon completion of this Next.js course, you will become proficient in web development fundamentals, React essentials, and advanced Next.js concepts. Through hands-on experience, master server-side rendering, client-side rendering, dynamic routing, and performance and scalability in real-world scenarios. What you will learn Master SSR, CSR, and SSG for optimized web development Explore React basics and advanced component development in Next.js Implement Next.js best practices for efficient and scalable web applications Learn to create dynamic routes for versatile content handling Deploy fully functional applications using Vercel and Git/GitHub workflows Enhance applications for search engines and social platforms through metadata and SEO practices Audience This Next.js course is tailored for a diverse audience, catering to both entry-level and seasoned developers. Ideal for junior developers, it provides a strong foundation in web development fundamentals, React basics, and advanced Next.js concepts. Intermediate developers can enhance their skills and gain mastery in the latest features of Next.js. Senior web developers seeking to stay updated with modern concepts will find valuable insights for optimizing web applications. No programming experience is required, but basic web development and JavaScript understanding is desirable for the course. About the Author Clarian North: Clarian North is a recognized industry-certified instructor, CEO of Orbital LLC, and a senior project engineer with over 90K enrolments worldwide. His students have gone on to work for some of the biggest production companies such as Universal, Google, Amazon, Warner, and the BBC. He has contributed to viral streams, grown a unique digital imprint in over 80 countries, and been featured in Rolling Stone, Billboard, Guardian, Bloomberg, and Vice. He has worked for majors, indies, and international publishing houses, including Grammy-nominated and award-winning productions, mixing for Emirates Airline Inflight Radio, and producing for Kompakt Records. He is dedicated to giving accessible and comprehensive tech courses, teaching complex subject matter with clear and example-based explanations, and guiding students through complex techniques with just a computer and free software.
    Note: Online resource; title from title details screen (O'Reilly, viewed January 31, 2024)
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  • 3
    Online Resource
    Online Resource
    Master ChatGPT and OpenAI APIs by building AI tools in Python (2024)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781835885628 , 1835885624
    Language: English
    Pages: 1 online resource (1 video file (11 hr., 11 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3
    Keywords: Artificial intelligence ; Python (Computer program language) ; Intelligence artificielle ; Python (Langage de programmation) ; artificial intelligence ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: Embark on a transformative learning experience with 'Master ChatGPT and OpenAI APIs By Building AI Tools in Python.' This immersive course takes you from the basics of ChatGPT and OpenAI's potent APIs through a journey of building dynamic AI-powered tools. Discover the magic behind ChatGPT's conversational prowess and dive deep into the neural networks and transformers that make it tick. You'll start by creating and managing your ChatGPT account, understanding the model's anatomy, and grasping the limitations and capabilities of AI language models. Transitioning from theory to hands-on practice, the course guides you through content creation, code generation, and the intricacies of prompt engineering. Moreover, you'll venture into the realms of generative AI with Midjourney, craft AI-driven applications, and harness the synergy of OpenAI and DALL-E for on-the-fly image generation. This course demystifies the AI concepts crucial in today's technology landscape, providing you with the skills to innovate and excel in the burgeoning field of AI. What you will learn Navigate the foundational elements of ChatGPT and OpenAI APIs Generate creative content and code with ChatGPT's language model Design and implement AI applications with user-friendly interfaces Master the art of prompt engineering for optimized AI interactions Build AI-powered tools and images using OpenAI and DALL-E Develop secure, intelligent applications with advanced Python techniques Audience This course welcomes everyone from entrepreneurs to artists and developers, aiming to learn about cutting-edge AI technologies and build AI-powered applications. Basic programming knowledge is preferred but not mandatory, making this course accessible to a wide range of learners. About the Author Paulo Dichone: Paulo Dichone, a seasoned software engineer and AWS Cloud Practitioner, is renowned for his expertise in Android, Flutter, and AWS, as well as being a best-selling instructor. Paulo has successfully imparted his knowledge to over 200,000 students across 175 countries, specializing in mobile app development for Android and iOS, web development, and AWS Cloud. His teaching philosophy centers on empowering students to excel as developers and AWS cloud practitioners, regardless of their prior experience. Beyond his professional pursuits, Paulo is devoted to his family, enjoys playing the guitar and mandolin, and loves to travel. He is committed to guiding students to achieve their highest potential in the tech industry.
    Note: Online resource; title from title details screen (O'Reilly, viewed March 4, 2024)
    URL: lizenzpflichtig
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    Online Resource
    MPI Ethno. Forsch.
  • 4
    Online Resource
    Online Resource
    Mastering REST APIs with FastAPI (2024)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781835464694 , 1835464696
    Language: English
    Pages: 1 online resource (1 video file (8 hr., 44 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.3
    Keywords: Application program interfaces (Computer software) ; Software architecture ; Python (Computer program language) ; Interfaces de programmation d'applications ; Architecture logicielle ; Python (Langage de programmation) ; APIs (interfaces) ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: This course offers a detailed exploration of FastAPI, a cutting-edge Python framework for API development. The course starts with basic API and REST principles, quickly advancing to practical application for a thorough understanding of both theory and practice. The curriculum progresses logically, starting with the basics of FastAPI, including app setup, API routing, linting, and formatting. Participants will create a social media API, manage post and comments, and learn code organization with APIRouter, followed by practical testing experience using pytest. A significant portion of the course focuses on asynchronous databases, vital for scalable application development. It covers database setup, connection, and integration within FastAPI. The course also delves into Python logging techniques, crucial for debugging and monitoring FastAPI applications. It also covers user authentication, an essential element in modern web apps. It includes practical training on JWTs, password hashing, authentication management, and database user relationships, alongside addressing many-to-many database relationships and user email confirmation strategies. In later stages, the course addresses advanced topics like file uploads, background image generation tasks, and deployment methodologies, including continuous integration with GitHub Actions. What you will learn Build and structure a FastAPI application Implement and test RESTful APIs with FastAPI Manage asynchronous database operations Configure and utilize Python logging in FastAPI Secure applications with user authentication and JWTs Handle complex database relationships Deploy FastAPI applications and manage them effectively Audience This course is ideal for aspiring back-end developers, testers looking to integrate automation into their workflows, and front-end developers seeking a deeper understanding of server-side processes. This course will particularly benefit those with a basic grasp of programming and a desire to specialize in the fast-paced realm of web development, API construction, and database management using FastAPI. Prior programming experience in any language is recommended; beginners should consider a basic Python course first, as all required software is provided for free. About the Author Jose Salvatierra Fuentes: Jose, a passionate educator in the realm of coding and software development, has dedicated over 7 years to teaching online. He founded Teclado with a vision to democratize software development education, striving to ensure comprehensive understanding for his students. His approach makes learning coding a clear, rewarding journey, connecting the dots that once seemed obscure. Specializing in Python and JavaScript, Jose excels in web and backend development. He's proficient in various libraries and frameworks, including Flask, React, React Native, and AngularJS. His expertise extends to working with UNIX systems, MongoDB, PostgreSQL, and crafting advanced system architectures. Jose's commitment is to make the learning process both efficient and enjoyable, guiding students to mastery in software development.
    Note: Online resource; title from title details screen (O'Reilly, viewed January 23, 2024)
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  • 5
    Online Resource
    Online Resource
    Abstracting with functions (2024)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781836204459 , 1836204450
    Language: English
    Pages: 1 online resource (1 video file (3 hr., 8 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.1/17
    Keywords: Python (Computer program language) ; Application software Development ; Python (Langage de programmation) ; Logiciels d'application ; Développement ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: """Abstracting with Functions"" is a meticulously curated video course designed for technical professionals eager to master the art of function creation in Python. Through a comprehensive series of videos, learners are taken on a journey that begins with the basics of what functions are and why they are pivotal in programming. The course underscores the significance of functions in collecting logic into reusable chunks, thereby fostering more readable and maintainable codebases. Starting with an introductory overview, the course swiftly moves to dissect the anatomy of functions, from the simplest forms without arguments to more complex functions featuring multiple positional and keyword arguments. Each episode, hosted by dynamic duos such as Aubri and Ronnie or Justin and Zach, not only discusses the syntax and theoretical aspects but also delves into practical demonstrations and the subtleties of function creation, such as edge cases and argument types. The importance of understanding functions is also linked to professional development, highlighting their relevance in networking and certification exams. By the end of the course, learners will have a solid grasp of how to efficiently abstract logic through functions, enabling the construction of more sophisticated and scalable programs. What you will learn Understand the fundamental concept of functions. Explore the syntax and creation of functions in Python. Distinguish between various types of functions. Learn advanced topics such as keyword arguments. Use mixed arguments to enhance function versatility. Grasp the significance of functions in different contexts. Audience Individuals at the beginning of their coding journey who want to learn best practices early on, and those with some experience in Python or other programming languages looking to deepen their understanding of functions and how to use them more effectively in their projects will find this course quite useful. About the Authors ACI Learning: ACI Learning trains leaders in Cybersecurity, Audit, and Information Technology. Whether starting an IT career, mastering a profession, or developing a team, they provide essential support at every step. Justin Dennison: Justin leads AWS and developer content creation for ITProTV. He has experience in multiple programming languages. His certifications include AWS Certified Solutions Architect -- Associate, AWS Certified Developer -- Associate, AWS Certified Cloud Practitioner, Oracle Certified Associate, Java SE 7 Programmer. Zachary Memos: Zachary Memos is a show host with 30+ years of on-camera experience. He brings his wit and charm to the camera while helping bring out the best in the ITProTV subject matter experts.".
    Note: Online resource; title from title details screen (O'Reilly, viewed April 23, 2024)
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  • 6
    Online Resource
    Online Resource
    Object oriented Python (2024)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781836204473 , 1836204477
    Language: English
    Pages: 1 online resource (1 video file (4 hr., 34 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Python (Langage de programmation) ; Programmation (Informatique) ; computer programming ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: An immersive video course designed to introduce and deepen your understanding of Object-Oriented Programming (OOP) principles within the Python ecosystem. Through a hands-on approach, instructors Vonne and Justin guide you from the foundational setup and OOP basics--encapsulation, abstraction, inheritance, and polymorphism--to the creation of a dynamic text-based game, MonsterSlash. This course is structured to enhance your programming skills by applying OOP techniques to reduce code redundancy, promote reusability, and streamline your coding workflow. You'll embark on a project-driven learning path that not only solidifies theoretical concepts but also puts them into practice by developing a fully functional game. As the course progresses, you'll refine your game, add complexity, and implement advanced OOP strategies, culminating in version 2 of MonsterSlash that features enhanced gameplay elements. Whether you're a beginner eager to explore programming or an intermediate looking to sharpen your OOP skills in Python, this course offers valuable insights and skills for your development arsenal. What you will learn Set up your Python environment for OOP development. Understand and apply the four pillars of OOP in Python. Create, extend, and refine classes and objects. Develop a text-based game from scratch using OOP principles. Employ inheritance and composition to optimize your code. Refactor and enhance your game with advanced OOP techniques. Audience This course is ideal for individuals interested in Python programming, especially those curious about object-oriented programming. Beginners will find the course accessible, while intermediate programmers can deepen their OOP knowledge. Prior exposure to basic Python syntax is helpful but not required. About the Authors ACI Learning: ACI Learning trains leaders in Cybersecurity, Audit, and Information Technology. Whether starting an IT career, mastering a profession, or developing a team, they provide essential support at every step. Justin Dennison: Justin leads AWS and developer content creation for ITProTV. He has experience in multiple programming languages. His certifications include AWS Certified Solutions Architect -- Associate, AWS Certified Developer -- Associate, AWS Certified Cloud Practitioner, Oracle Certified Associate, Java SE 7 Programmer. Vonne Smith: Vonne leads the content development for the OfficeProTV and CreativeProTV channels. She has over a decade of experience teaching Office and Adobe applications both online and in the classroom. Certifications: Microsoft Office Master 2016.
    Note: Online resource; title from title details screen (O'Reilly, viewed April 23, 2024)
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  • 7
    Online Resource
    Online Resource
    Create your own ChatGPT clone using Python (2024)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781836206071 , 1836206070
    Language: English
    Pages: 1 online resource (1 video file (2 hr., 27 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: ChatGPT ; Python (Computer program language) ; Computer programming ; Artificial intelligence ; Python (Langage de programmation) ; Programmation (Informatique) ; Intelligence artificielle ; computer programming ; artificial intelligence ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: "Unlock the world of conversational AI with ""Create Your Own ChatGPT Clone using Python,"" a comprehensive video course designed to teach you the intricacies of AI model interactions. Starting with a solid introduction and setup requirements, this course swiftly moves into hands-on exercises where you'll engage with the ChatGPT API using Python. You'll not only learn about API parameters and endpoints but also how to weave these components into a responsive Python FastAPI service. Transitioning from Python to front-end development, the course empowers you to create a React project, giving life to your ChatGPT clone with engaging styles and functionalities. The journey continues into the nuances of fine-tuning models, where you'll tailor ChatGPT solutions to fit specific needs, offering personalized experiences. The course culminates in strategic model selection, ensuring you're equipped to choose the most effective GPT model for your project's requirements, capped off with a cohesive summary tying all learned concepts together. What you will learn Navigate the setup for ChatGPT API interaction. Create a Python FastAPI for ChatGPT. Construct and style a ChatGPT clone in a React environment. Customize ChatGPT models through fine-tuning techniques. Select the optimal GPT model for specific project needs. Synthesize course knowledge in a comprehensive project. Audience Geared towards Python developers keen on building AI chatbots, and AI and NLP enthusiasts looking to delve into chatbot development, this course suits students and professionals eager for hands-on AI and Python experience. A foundational grasp of Python, React, and basic API interactions is assumed, catering to innovators who want to unlock the potential of conversational AI. About the Author Eduonix Learning Solutions: Eduonix Learning Solutions is at the forefront of technology training, boasting a vast global reach with over 1 million students across 200+ courses. With a rich history spanning over a decade, Eduonix's mission is to deliver industry-standard, high-quality training content created by a team of seasoned industry professionals. Their comprehensive curriculum covers a wide range of technologies, from Web and Mobility to Enterprise, Database, and Server Administration. Eduonix is dedicated to teaching technology in the context of real-world professional applications, ensuring that learners are equipped with the skills needed to excel in today's tech-driven landscape.".
    Note: Online resource; title from title details screen (O'Reilly, viewed April 22, 2024)
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  • 8
    Online Resource
    Online Resource
    Social media automation using Python (2023)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781837630875 , 1837630879
    Language: English
    Pages: 1 online resource (1 video file (2 hr., 39 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Social media ; Computer programming ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Welcome to this course on automating social media applications using Python. Let's learn the basic concepts required for automating our routine social media tasks. We will begin with learning to automate WhatsApp and explore how to automatically send messages to individuals and groups using Python. You will learn to automate sending emails to random users with just a few lines of code. Learn to schedule tasks using Python to implement different social media projects. Explore email automation with Smtplib and link Gmail with SMTP. We will explore how to fetch and download different stats from YouTube channels as CSV or other file formats. Finally, you will learn to post various types of content on Facebook pages, delete posts, and comment on posts. The course, however, does not cover Python programming lessons separately. Upon completing the course, you can automate social media platforms such as WhatsApp, YouTube, Facebook, and Gmail. Create automated posts and comments, post and delete content, schedule tasks, and comprehensively advance your social media automation skills. What You Will Learn Automate WhatsApp, install the toolkit, schedule and send messages Link Gmail with SMTP, create email, attach files and send Schedule, install, import, and code a simple scheduler Create a YouTube API key and fetch channel and playlist information Automate Facebook, post photos with captions, and comment on a post Understand and implement automation packages and libraries Audience This course is designed for beginners with some programming experience or even those who need to know about data analysis, data manipulation, and more. This course is for individuals wanting to understand and implement automation packages and libraries, master scheduling tasks, automate emails, automate WhatsApp, automate YouTube data, and automate Facebook posts. Basic to intermediate Python programming knowledge is required for the course. About The Author AI Sciences: AI Sciences is a group of experts, PhDs, and practitioners of AI, ML, computer science, and statistics. Some of the experts work in big companies such as Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM. They have produced a series of courses mainly dedicated to beginners and newcomers on the techniques and methods of machine learning, statistics, artificial intelligence, and data science. Initially, their objective was to help only those who wish to understand these techniques more easily and to be able to start without too much theory. Today, they also publish more complete courses for a wider audience. Their courses have had phenomenal success and have helped more than 100,000 students master AI and data science.
    Note: "Published in January 2023.". - Online resource; title from title details screen (O'Reilly, viewed February 20, 2023)
    URL: lizenzpflichtig
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  • 9
    Online Resource
    Online Resource
    Data science : Time series forecasting with Facebook Prophet in Python (2023)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781803237466 , 1803237465
    Language: English
    Pages: 1 online resource (1 video file (2 hr., 12 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Facebook (Electronic resource) ; Python (Computer program language) ; Time-series analysis Data processing ; Machine learning ; R (Computer program language) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Prophet enables Python and R developers to build scalable time series forecasts. This course will help you implement Prophet's cutting-edge forecasting techniques to model future data with higher accuracy and with very few lines of code. In this course, you will learn how to use Facebook Prophet to do time series analysis and forecasting. You will learn how the Prophet works under the hood (that is, what are its modeling assumptions?) and the Prophet API (that is, how to write the code). This course is a practice-oriented course, demonstrating how to prepare your data for Prophet, fit a model, and use it to forecast, analyze the results, and evaluate the model's predictions. We will apply Prophet to a variety of datasets, including store sales and stock prices. You will learn how to use Prophet to plot the model's in-sample predictions and forecast. Then, learn how to plot the components of the fitted model. You will also learn how to deal with outliers, missing data, and non-daily (for example, monthly) data. By the end of this course, you will be able to use Prophet confidently to forecast your data. What You Will Learn Prepare your data (a Pandas dataframe) for Facebook Prophet Learn how to fit a Prophet model to a time series Plot the components of the fitted model Model holidays and exogenous regressors Evaluate your model with forecasting metrics Learn how to do changepoint detection with Prophet Audience Anyone interested in data science, machine learning, or who wishes to use time series analysis on their own data should take this course. Good Python programming skills are required, as well as knowledge of Pandas, Dataframes, and preferably some familiarity with Scikit-Learn, though this is not required. About The Author Lazy Programmer: The Lazy Programmer is an AI and machine learning engineer with a focus on deep learning, who also has experience in data science, big data engineering, and full-stack software engineering. With a background in computer engineering and specialization in machine learning, he holds two master's degrees in computer engineering and statistics with applications to financial engineering. His expertise in online advertising and digital media includes work as both a data scientist and big data engineer. He has created deep learning models for prediction and has experience in recommendation systems using reinforcement learning and collaborative filtering. He is a skilled instructor who has taught at universities including Columbia, NYU, Hunter College, and The New School. He has web programming expertise, with experience in technologies such as Python, Ruby/Rails, PHP, and Angular, and has provided his services to multiple businesses.
    Note: Online resource; title from title details screen (O'Reilly, viewed March 20, 2023)
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  • 10
    Online Resource
    Online Resource
    Basics of chatbots with machine learning & Python (2023)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781837635092 , 1837635099
    Language: English
    Pages: 1 online resource (1 video file (3 hr., 4 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.33
    Keywords: Human-computer interaction ; Machine learning ; Python (Computer program language) ; Artificial intelligence ; Artificial intelligence ; Human-computer interaction ; Machine learning ; Python (Computer program language) ; Instructional films ; Internet videos ; Nonfiction films ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Chatbots are software applications used for online chat conversations through text or text-to-speech instead of providing direct contact with a live human agent. Chatbots are used in dialog systems for various purposes, including customer service, request routing, or information gathering. This course begins with a brief overview of chatbots, their need, and the types of chatbots. We will explore rule-based versus self-learning chatbots. We will understand the working mechanism of chatbots. We will explore machine learning-based chatbots and understand the ML-based architecture of chatbots. You will learn about the purpose of ML-based chatbots and their impact. We will get an overview of the Natural Language Toolkit (NLTK). You will learn to install packages and create a corpus with Python. We will delve into text preprocessing and helper function deployment, generate responses, and implement term-frequency times inverse document-frequency. We will train and test rule-based chatbots and finally work on a project developing an artificial intelligence question-answer chatbot using NLTK. Upon course completion, you will be able to relate the concepts and theories for chatbots in various domains, understand and implement machine learning models for building real-time chatbots, and evaluate machine learning models in chatbots. What You Will Learn Learn about chatbot types, rule-based and self-learning chatbots Learn text preprocessing and develop helper functions with Python Explore the impact and overview of the Natural Language Toolkit Gain hands-on practice, generate text in Python to develop chatbots Explore testing and training of chatbot with machine learning Implement term-frequency times inverse document-frequency hands-on Audience This course delivers content to people wishing to advance their skills in applied machine learning, master data analysis with machine learning, build customized chatbots for their applications, and implement machine learning algorithms for chatbots. This course is for you if you are passionate about rule-based and conversational chatbots. Machine learning practitioners, research scholars, and data scientists can benefit from the course. No prior knowledge of chatbots, or machine learning, is needed. You will need to know basic to intermediate Python coding, which is not taught separately in the course. About The Author AI Sciences: AI Sciences is a group of experts, PhDs, and practitioners of AI, ML, computer science, and statistics. Some of the experts work in big companies such as Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM. They have produced a series of courses mainly dedicated to beginners and newcomers on the techniques and methods of machine learning, statistics, artificial intelligence, and data science. Initially, their objective was to help only those who wish to understand these techniques more easily and to be able to start without too much theory. Today, they also publish more complete courses for a wider audience. Their courses have had phenomenal success and have helped more than 100,000 students master AI and data science.
    Note: "Published in February 2023.". - Online resource; title from title details screen (O'Reilly, viewed March 21, 2023)
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  • 11
    Online Resource
    Online Resource
    Deep learning : deep neural network for beginners using Python (2023)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781837633579 , 1837633576
    Language: English
    Pages: 1 online resource (1 video file (6 hr., 28 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3/1
    Keywords: Deep learning (Machine learning) ; Neural networks (Computer science) ; Python (Computer program language) ; Computer programming ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Are you ready to start your path to becoming a deep learning expert? Then this course is for you. This course is step-by-step. In every new tutorial, we build on what we have already learned and move one extra step forward, and then we assign you a small task that is solved at the beginning of the next video. We start by teaching the theoretical part of the concept, and then implement everything as it is practically using Python. This comprehensive course will be your guide to learning how to use the power of Python to train your machine such that your machine starts learning just like humans, and based on that learning, your machine starts making predictions as well! We will be using Python as a programming language in this course, which is the hottest language nowadays if we talk about machine learning. Python will be taught from the elementary level up to an advanced level so that any machine learning concept can be implemented. You will also learn various steps of data preprocessing, which allows us to make data ready for machine learning algorithms. You will learn the general concepts of machine learning overall, which will be followed by the implementation of one of the essential ML algorithms, "Deep Neural Networks". Each concept of DNNs will be taught theoretically and will be implemented using Python. By the end of this course, you will be able to understand the methodology of DNNs with deep learning using real-world datasets. What You Will Learn Learn the basics of machine learning and neural networks Understand the architecture of neural networks Learn the basics of training a DNN using the Gradient Descent algorithm Learn how to implement a complete DNN using NumPy Learn to create a complete structure for DNN from scratch using Python Work on a project using deep learning for the IRIS dataset Audience This course is designed for anyone who is interested in data science or interested in taking their data-speak to a higher level. Students who want to master DNNs with real datasets in deep learning or who want to implement DNNs in realistic projects can also benefit from the course. You need to have a background in deep learning to get the best out of this course. About The Author AI Sciences: AI Sciences is a group of experts, PhDs, and practitioners of AI, ML, computer science, and statistics. Some of the experts work in big companies such as Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM. They have produced a series of courses mainly dedicated to beginners and newcomers on the techniques and methods of machine learning, statistics, artificial intelligence, and data science. Initially, their objective was to help only those who wish to understand these techniques more easily and to be able to start without too much theory. Today, they also publish more complete courses for a wider audience. Their courses have had phenomenal success and have helped more than 100,000 students master AI and data science.
    Note: "Published in January 2023.". - Online resource; title from title details screen (O'Reilly, viewed February 20, 2023)
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  • 12
    Online Resource
    Online Resource
    Advanced chatbots with deep learning and Python (2023)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781837632534 , 1837632537
    Language: English
    Pages: 1 online resource (1 video file (1 hr., 59 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.33
    Keywords: Human-computer interaction ; Machine learning ; Python (Computer program language) ; Artificial intelligence
    Abstract: AI-powered chatbots are also capable of automating various tasks, including sales and marketing, customer service, and administrative and operational tasks. In this course about developing advanced chatbots with deep learning, we will understand their applications and build from scratch using deep learning with Python The course begins with a brief overview and the fundamentals of deep learning for chatbots. We will understand and compare conventional chatbots with deep learning-based chatbots. Then, we will explore self-learning chatbots, including generative chatbots and retrieval chatbots. You will learn more about deep learning-empowered chatbot features and compare and distinguish the abilities of conventional chatbots and self-learning chatbots in real action. We will focus on chatbot development with deep learning, tokenization, setting up an Encoder-Decoder, implementing RNN-based model development, and finally, training, testing, and validating the chatbot we developed. Upon completing this course successfully, you will relate concepts and understand theories of chatbots in various domains, understand and implement deep learning models for building real-world chatbots, and evaluate deep learning-based chatbot models. What You Will Learn Relate the concepts and theories for chatbots in various domains Compare conventional chatbots with deep learning-based chatbots Understand deep learning algorithms for chatbots Implement deep learning models for building real-world chatbots Learn about tokenization and setting up an encoder-decoder Implement recurrent neural network-based model development Audience This course is designed for individuals looking to advance their skills in applied deep learning, acquire knowledge regarding the relationships of data analysis with deep learning, wish to build customized chatbots for their applications, learn to implement deep learning algorithms for chatbots, and are passionate about rule-based and self-learning chatbots. Deep learning practitioners/scholars working on chatbot concepts would benefit from this course. No prior knowledge of chatbots, deep learning, data analysis, or mathematics is needed. Basic to intermediate Python knowledge is required. About The Author AI Sciences: AI Sciences are experts, PhDs, and artificial intelligence practitioners, including computer science, machine learning, and Statistics. Some work in big companies such as Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM. AI sciences produce a series of courses dedicated to beginners and newcomers on techniques and methods of machine learning, statistics, artificial intelligence, and data science. They aim to help those who wish to understand techniques more easily and start with less theory and less extended reading. Today, they publish more comprehensive courses on specific topics for wider audiences. Their courses have successfully helped more than 100,000 students master AI and data science.
    Note: "Published in February 2023."
    URL: lizenzpflichtig
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  • 13
    Online Resource
    Online Resource
    Python for OOP : the A to Z OOP Python programming course (2023)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781805127956 , 1805127950
    Language: English
    Pages: 1 online resource (1 video file (4 hr., 1 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.1/17
    Keywords: Object-oriented programming (Computer science) ; Python (Computer program language) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Object-Oriented Programming (OOP) is a crucial paradigm in modern programming that allows developers to write efficient, modular, and scalable code. It helps in organizing code, creating reusable and maintainable code, and improving code readability. In this course, we will dive deep into OOP concepts and provide you with a solid understanding of the fundamentals, advanced topics, and real-world applications of OOP in Python. This course covers a wide range of topics, starting with the basics of OOP, including classes, objects, attributes, methods, and constructors. You will learn about encapsulation, abstraction, inheritance, and polymorphism, which are the building blocks of OOP. You will also explore advanced concepts such as class methods, static methods, operator overloading, and dunder methods, along with practical examples and exercises to solidify your understanding. To apply the concepts learned, you will build a real-world project, the Library Management System, where you will learn to create classes, objects, and methods for managing books and users. You will also gain hands-on experience with method overriding, multiple inheritances, and other advanced topics while building practical applications. By the end of this course, you will have a deep understanding of OOP concepts in Python, be able to build robust and scalable applications using OOP principles, and possess the skills to write clean, efficient, and maintainable Python code. What You Will Learn Understand the fundamentals of Object-Oriented Programming in Python Build real-world projects using OOP concepts in Python Apply polymorphism in object-oriented styles using multiple strategies Implement OOP principles to create reusable and maintainable Python code Build a Library Management System using OOP concepts Master the use of classes, objects, attributes, methods, and constructors in Python Audience This course is tailored for programmers and developers who aspire to deepen their understanding of Object-Oriented Programming (OOP) concepts and apply them in real-world applications. It is well-suited for beginners who are already familiar with Python basics and are looking to transition into OOP programming. Intermediate Python developers seeking to enhance their coding skills and learn advanced OOP topics will also find value in this course. Prior knowledge of Python programming concepts is required, including variables, data types, loops, and functions. If you are eager to learn and apply OOP principles practically in Python, this comprehensive course will provide you with the knowledge and skills needed to succeed. About The Author Meta Brains: Meta Brains is a professional training brand developed by a team of software developers and finance professionals who have a passion for finance, coding, and Excel. They bring together both professional and educational experiences to create world-class training programs accessible to everyone. Currently, they are focused on the next great revolution in computing: the Metaverse. Their ultimate objective is to train the next generation of talent so that we can code and build the metaverse together!.
    Note: Online resource; title from title details screen (O'Reilly, viewed May 23, 2023)
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  • 14
    Online Resource
    Online Resource
    Data science prerequisites : Numpy, Matplotlib, and Pandas in Python (2023)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781803241616 , 1803241616
    Language: English
    Pages: 1 online resource (1 video file (4 hr., 23 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Deep learning (Machine learning) ; Machine learning ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Welcome to the course where you will learn about the NumPy stack in Python, which is an important prerequisite for deep learning, machine learning, and data science. In this self-paced course, you will learn how to use NumPy, Matplotlib, Pandas, and SciPy to perform critical tasks related to data science and machine learning. This involves performing numerical computation and representing data, visualizing data with plots, loading in, and manipulating data using DataFrames, performing statistics and probability, and building machine learning models for classification and regression. In this course, we will first start with NumPy; we will understand the benefits of NumPy array and then we will look at some complicated matrix operations, such as products, inverses, determinants, and solving linear systems. Then we will cover Matplotlib. In this section, we will go over some common plots, namely the line chart, scatter plot, and histogram. We will also look at how to show images using Matplotlib. Next, we will talk about Pandas. We will look at how much easier it is to load a dataset using Pandas versus trying to do it manually. Then we will look at some data frame operations useful in machine learning, such as filtering by column, filtering by row, and the apply function. Later, you will learn about SciPy. In this section, you will learn how to do common statistics calculations, including getting the PDF value, the CDF value, sampling from a distribution, and statistical testing. Finally, we will also cover some basics of machine learning that will help us start our deep learning journey. By the end of the course, we will be able to confidently use the NumPy stack in deep learning and data science. What You Will Learn Understand supervised machine learning with real-world examples Understand and code using the NumPy stack Make use of NumPy, SciPy, Matplotlib, and Pandas to implement numerical algorithms Understand the pros and cons of various machine learning models Get a brief introduction to the classification and regression Learn how to calculate the PDF and CDF under the normal distribution Audience This course is designed for anyone who is interested in data science and machine learning, who knows Python and wants to take the next step into Python libraries for data science, or who is interested in acquiring tools to implement machine learning algorithms. One must have decent Python programming skills and a basic understanding of linear algebra and probability for this course. About The Author Lazy Programmer: The Lazy Programmer is an AI and machine learning engineer with a focus on deep learning, who also has experience in data science, big data engineering, and full-stack software engineering. With a background in computer engineering and specialization in machine learning, he holds two master's degrees in computer engineering and statistics with applications to financial engineering. His expertise in online advertising and digital media includes work as both a data scientist and big data engineer. He has created deep learning models for prediction and has experience in recommendation systems using reinforcement learning and collaborative filtering. He is a skilled instructor who has taught at universities including Columbia, NYU, Hunter College, and The New School. He has web programming expertise, with experience in technologies such as Python, Ruby/Rails, PHP, and Angular, and has provided his services to multiple businesses.
    Note: Online resource; title from title details screen (O'Reilly, viewed April 11, 2023)
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  • 15
    Online Resource
    Online Resource
    A practical approach to timeseries forecasting using Python (2023)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781837632510 , 1837632510
    Language: English
    Pages: 1 online resource (1 video file (12 hr., 26 min.)) , sound, color.
    Edition: [First edition].
    DDC: 519.55
    Keywords: Time-series analysis Data processing ; Time-series analysis Computer programs ; Python (Computer program language)
    Abstract: Have you ever wondered how weather predictions, population estimates, and even the lifespan of the universe are made? Discover the power of time series forecasting with state-of-the-art ML and DL models. The course begins with the fundamentals of time series analysis, including its characteristics, applications in real-world scenarios, and practical examples. Then progress to exploring data analysis and visualization techniques for time series data, ranging from basic to advanced levels, using powerful libraries such as NumPy, Pandas, and Matplotlib. Python will be utilized to assess various aspects of your time series data, such as seasonality, trend, noise, autocorrelation, mean over time, correlation, and stationarity. Additionally, you will learn how to pre-process time series data for utilization in applied machine learning and recurrent neural network models, which will enable you to train, test, and assess your forecasted results. Finally, you will acquire an understanding of the applied ML models, including their performance evaluations and comparisons. In the RNNs module, you will be building GRU, LSTM, Stacked LSTM, BiLSTM, and Stacked BiLSTM models. By the end of this course, you will be able to understand time series forecasting and its parameters, evaluate the ML models, and evaluate the model and implement RNN models for time series forecasting. What You Will Learn Learn data analysis techniques and handle time series forecasting Implement data visualization techniques using Matplotlib Evaluate applied machine learning in time series forecasting Look at auto regression, ARIMA, Auto ARIMA, SARIMA, and SARIMAX Learn to model LSTM, Stacked LSTM, BiLSTM, and Stacked BiLSTM models Implement ML and RNN models with three state-of-the-art projects Audience No prior knowledge of DL, data analysis, or math is required. You will start from the basics and gradually build your knowledge of the subject. Only the basics of Python are required. This course is designed for both beginners with some programming experience and even those who know nothing about data analysis, ML, and RNNs. The course is suitable for individuals who want to advance their skills in ML and DL, master the relation of data science with time series analysis, implement time series parameters and evaluate their impact on it and implement ML algorithms for time series forecasting. About The Author AI Sciences: AI Sciences are experts, PhDs, and artificial intelligence practitioners, including computer science, machine learning, and Statistics. Some work in big companies such as Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM. AI sciences produce a series of courses dedicated to beginners and newcomers on techniques and methods of machine learning, statistics, artificial intelligence, and data science. They aim to help those who wish to understand techniques more easily and start with less theory and less extended reading. Today, they publish more comprehensive courses on specific topics for wider audiences. Their courses have successfully helped more than 100,000 students master AI and data science.
    Note: "Published in March 2022."
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  • 16
    Online Resource
    Online Resource
    Power BI Masterclass : 8: Python, finance, and advanced DAX (2023)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781835085400 , 1835085407
    Language: English
    Pages: 1 online resource (1 video file (3 hr., 32 min.)) , sound, color.
    Edition: [First edition].
    DDC: 658.4/038011
    Keywords: Microsoft Power BI (Computer file) ; Business intelligence Computer programs ; Information visualization Computer programs ; Dashboards (Management information systems) ; Python (Computer program language) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Microsoft Power BI is a powerful business analytics/data visualization tool that enables users to connect to various data sources, create interactive reports and dashboards, and gain insights from the data. With its intuitive interface and robust features, Power BI empowers users to make data-driven decisions and effectively communicate information with stakeholders. The course begins with setting up the Python environment for Power BI and then dives into using Python for data visualization in Power BI. It covers advanced DAX expressions and calculations, exploring a business dataset. You will also learn how to leverage Python libraries for data science in Power BI and create a balance sheet structure. The course includes applying custom visuals and culminates in creating a final dashboard. However, the Python concepts covered in this course cannot be considered comprehensive, only content related to Power BI usage requirements. Upon completing the course, you will gain advanced knowledge and skills in using Power BI for data visualization, analysis, and science. You will be proficient in setting up the Python environment in Power BI, leveraging Python for data visualization, and applying advanced DAX expressions and calculations, enabling you to effectively analyze/present data in various business scenarios. What You Will Learn Learn to integrate Python for data visualization in Power BI Master advanced DAX expressions and calculations Apply custom visuals to enhance your reporting capabilities Create balance sheet structures and evaluate balances using DAX Utilize Python's data science libraries for analysis in Power BI Build a comprehensive dashboard for effective data presentation Audience This course suits those interested in combining Power BI and Python and anyone wanting to explore Microsoft Power BI. If you want to excel in your work, explore new data analytics career opportunities, or lay the foundation for a successful future in the data era, this course equips you with the necessary skills. It also appeals to individuals seeking a better tool than QlikView and IBM Cognos. Prerequisites include Power BI, free to download with no additional costs, and a willingness to learn and explore new opportunities; all necessary files and materials will be provided. About The Author Dan We: Daniel Weikert is a 33-year-old entrepreneur, data enthusiast, consultant, and trainer. He is a master's degree holder certified in Power BI, Tableau, Alteryx (Core and Advanced), and KNIME (L1-L3). He is currently working in the business intelligence field and helps companies and individuals obtain vital insights from their data to deliver long-term strategic growth and outpace their competitors. He has a passion for learning and teaching. He is committed to supporting other people by offering them educational services and helping them accomplish their goals, gain expertise in their profession, or explore new careers.
    Note: Online resource; title from title details screen (O'Reilly, viewed August 3, 2023)
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  • 17
    Online Resource
    Online Resource
    PyTorch ultimate 2023 : from basics to cutting-edge (2023)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781801070089 , 1801070083
    Language: English
    Pages: 1 online resource (1 video file (17 hr., 39 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3/2
    Keywords: Neural networks (Computer science) ; Machine learning ; Python (Computer program language) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: PyTorch is a Python framework developed by Facebook to develop and deploy deep learning models. It is one of the most popular deep-learning frameworks nowadays. You will begin with learning the deep learning concept. Dive deeper into tensor handling, acquiring the finesse to create and manipulate tensors while leveraging PyTorch's automatic gradient calculation through Autograd. Then transition to modeling by constructing linear regression models from scratch. After that, you will dive deep into classification models, mastering both multilabel and multiclass. You will then see the theory behind object detection and acquire the prowess to build object detection models. Embrace the cutting edge with YOLO v7, YOLO v8, and faster RCNN, and unleash the potential of pre-trained models and transfer learning. Delve into RNNs and look at recommender systems, unlocking matrix factorization techniques to provide personalized recommendations. Refine your skills in model debugging and deployment, where you will debug models using hooks, and navigate the strategies for both on-premise and cloud deployment. Finally, you will explore ChatGPT, ResNet, and Extreme Learning Machines. By the end of this course, you will have learned the key concepts, models, and techniques, and have the confidence to craft and deploy robust deep-learning solutions. What You Will Learn Grasp deep learning concepts and install tools/packages/IDE/libraries Master CNN theory, image classification, layer dimensions, and transformations Dive into audio classification using torchaudio and spectrograms Do object detection with the help of YOLO v7, YOLO v8, and Faster RCNN Learn word embeddings, sentiment analysis, and pre-trained NLP models Deploy models using Google Cloud and other strategies Audience This course is ideal for Python developers and data enthusiasts seeking to expand their skills. This will also benefit aspiring data scientists, machine learning engineers, AI enthusiasts, and anyone intrigued by the transformative potential of deep learning. Whether you are a beginner or possess some prior knowledge, this course offers a smooth progression that will empower you to develop, deploy, and innovate with deep learning models using PyTorch. Basic Python knowledge is required to fully engage with the material. About The Author Bert Gollnick: Bert Gollnick is a proficient data scientist with substantial domain knowledge in renewable energies, particularly wind energy. With a rich background in aeronautics and economics, Bert brings a unique perspective to the field. Currently, Bert holds a significant role at a leading wind turbine manufacturer, leveraging his expertise to contribute to innovative solutions. For several years, Bert has been a dedicated instructor, offering comprehensive training in data science and machine learning using R and Python. The core interests of Bert lie at the crossroads of machine learning and data science, reflecting a commitment to advancing these disciplines.
    Note: "Updated September 2023.". - Online resource; title from title details screen (O'Reilly, viewed October 10, 2023)
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  • 18
    Online Resource
    Online Resource
    Python GUI development with Tkinter : build pro desktop apps! (2023)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781835082133 , 1835082130
    Language: English
    Pages: 1 online resource (1 video file (2 hr., 40 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.4/37
    Keywords: Graphical user interfaces (Computer systems) Programming ; Python (Computer program language) ; Object-oriented programming (Computer science) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Tkinter is a powerful and widely-used GUI toolkit for Python. It allows developers to create desktop apps with interactive user interfaces. With Tkinter, developers can design windows, buttons, menus, text boxes, and other widgets, making it an essential tool for building visually appealing and user-friendly applications. Python's ease of use, combined with Tkinter's versatility, make it an excellent choice for GUI development, enabling programmers to develop desktop apps in Python The course content includes an introductory section on GUI programming and Tkinter. It then proceeds to establish a strong foundation by exploring basic Tkinter widgets. As the course advances, it delves into more advanced widgets and layouts. Students will learn to master event handling to create interactive interfaces. The course covers the design and structure of robust GUI applications, customization of widget and styling, and best practices for writing efficient code. Real-world projects provide practical applications of the learned knowledge. Upon completion, we will be proficient in GUI programming with Tkinter, possess knowledge of basic and advanced widgets, understand event handling, be skilled in designing robust applications, customizing widgets, and implementing best coding practices, and have hands-on experience with real-world projects. What You Will Learn Learn the fundamentals of GUI development and the Tkinter library Create visually appealing interfaces with Tkinter widgets Master layout management for responsive applications Explore advanced Tkinter widgets and techniques Handle user interactions and employ event-driven programming Customize widget appearance and write efficient code for practical projects Audience This course is for Python developers aiming to venture into GUI development, building desktop apps with Python and Tkinter, computer science or software engineering students, and anyone keen to create useful and interactive desktop applications. Individuals looking to enhance their portfolio with user-friendly interfaces and those enthusiastic about exploring Python's GUI programming can benefit. Prerequisites include an eagerness to learn and experiment with GUI development using Tkinter, basic math skills, and a passion for learning. Prior experience in any programming language is desirable. About The Author Meta Brains: Meta Brains is a team of passionate software developers and finance professionals. They provide professional training programs that combine their expertise in coding, finance, and Excel. With a focus on the Metaverse, they aim to equip learners with the necessary skills to participate in the next computing revolution. Their inclusive approach ensures accessibility to everyone, fostering a community that collaboratively codes and builds the future of the Metaverse.
    Note: "Published in August 2023.". - Online resource; title from title details screen (O'Reilly, viewed August 14, 2023)
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  • 19
    Online Resource
    Online Resource
    Python : complete Python, Django, data science and ML guide (2023)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781835465141 , 1835465145
    Language: English
    Pages: 1 online resource (1 video file (50 hr., 34 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Machine learning ; Computer programming ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: "Join us on an immersive Python programming journey, spanning over 50 hours of learning. Whether you're a novice or experienced, this course equips you with vital Python skills for careers and projects. Starting from the basics, grasp Python's core principles and proficiency in real-world functions. As Python's popularity grows, this course readies you for the rising demand for Python developers. You'll practice hand-on examples using Python's interpreter and Visual Studio Code with Code Runner to solidify your skills. With a focus on Data Science and Machine Learning, you'll master essential packages such as NumPy, Pandas, Matplotlib, and Scikit-learn, using the versatile Jupyter Notebook. The course extensively covers Python's fundamental aspects, spanning variables, lists, dictionaries, and venturing into advanced topics like classes, loops, modules, and creating virtual environments. The goal is to provide you with a solid Python foundation. You'll also gain insight into functional and object-oriented Python programming, making you a versatile coder. The course is thoughtfully structured, explaining not just ""how"" but also ""why"" we use specific methods and best practices. By course end, you'll harness Python's full potential for web and mobile app development, data science, machine learning, and game creation. What You Will Learn Grasp concepts such as data types, loops, and conditional statements to build a robust coding foundation Understand OOP principles like inheritance, encapsulation, and polymorphism for streamlined code Manipulate files, directories, and efficiently manage external modules through Python Master real-world datasets with NumPy, Pandas, Matplotlib and more Ensure code reliability through Python's error handling and master the nuances of PIP and virtual project isolation Audience This comprehensive Python course is tailored for a diverse audience. It's an excellent choice for beginners taking their first steps in programming. If you're interested in data science and machine learning, this course equips you with essential skills. Web developers can leverage Python for building web applications. Moreover, if you're keen on tasks involving machine learning and data processing, this course is for you. Game developers looking to create games using Python and Pygame will find this course invaluable. About The Author Bogdan Stashchuk: Bogdan Stashchuk has over 20 years of experience as a software engineering instructor. He excels at breaking down complex topics into easy-to-follow steps. His courses are designed with hands-on exercises, ensuring that learners can actively participate and apply what they learn. From start to finish, students can follow along and complete tasks just as Bogdan demonstrates in his lectures. He also includes challenging assignments with detailed solutions. This approach helps learners understand and remember the material long after they've completed the course. Through his dedication and expertise, Bogdan ensures a valuable and effective learning experience for everyone.".
    Note: "Updated October 2023.". - Online resource; title from title details screen (O'Reilly, viewed November 15, 2023)
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  • 20
    Online Resource
    Online Resource
    Python for data visualization : a beginner's guide (2023)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781805127598 , 1805127594
    Language: English
    Pages: 1 online resource (1 video file (3 hr., 42 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Information visualization ; Computer programming ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Python-based data visualization uses the Python programming language and its libraries to transform data into visual representations, such as charts, graphs, and interactive dashboards. Python's libraries, including Matplotlib, Seaborn, Plotly, and Bokeh, offer customizable plot types and interactive features to craft compelling visual narratives. Through data storytelling and customization, Python shares insights and effectively communicates them, making it an indispensable skill for anyone working with data. In this course, we will begin by grasping the importance of data visualization and exploring essential Python libraries such as Matplotlib, Seaborn, and Plotly. You will learn to customize and enhance visualizations, adjust colors, labels, and legends, and understand the principles of effective data storytelling. The course delves into advanced topics such as creating interactive dashboards and dynamic data plots. We will work on practical projects and real-world examples to equip us with the skills to turn raw data into informative visuals using Python. Upon completion, we will master Python-based data visualization from core principles to practical skills, Matplotlib, Seaborn, and Plotly, and transform raw data into compelling visuals. We will acquire tools to create visuals, convey insights, and make data-driven decisions with confidence. What You Will Learn Understand the importance/principles of effective data visualization Learn Matplotlib, Seaborn, and Plotly to create various visualizations Learn to tailor colors, labels, and styles to enhance visuals Craft data visualizations to create compelling narratives Create engaging and user-friendly interactive data displays Explore geospatial data mapping and location-based visualizations Audience This course caters to a wide audience from beginners with no programming experience to experienced data professionals, programmers looking to expand their skillsets, business professionals seeking practical data visualization knowledge, and students/researchers aiming to strengthen their data visualization proficiency using Python. There are no specific prerequisites for this course. However, having a basic understanding of mathematics and readiness to learn are helpful attributes for successfully completing the course. About The Author Meta Brains: Meta Brains is a professional training brand developed by a team of software developers and finance professionals who have a passion for finance, coding, and Excel. They bring together both professional and educational experiences to create world-class training programs accessible to everyone. Currently, they're focused on the next great revolution in computing: The Metaverse. Their ultimate objective is to train the next generation of talent so that we can code and build the metaverse together!.
    Note: "Updated for September 2023.". - Online resource; title from title details screen (O'Reilly, viewed October 11, 2023)
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  • 21
    Online Resource
    Online Resource
    Build a super advanced trading bot on DYDX hosted on AWS with Python (2023)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781835083857 , 1835083854
    Language: English
    Pages: 1 online resource (1 video file (7 hr., 51 min.)) , sound, color.
    Edition: [First edition].
    DDC: 332.028541
    Keywords: Artificial intelligence Financial applications ; Python (Computer program language) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: In this course, you will learn how to develop an end-to-end decentralized trading bot using Python, interact with Telegram for real-time notifications, and leverage the capabilities of AWS to run your code 24/7 in the cloud. The course begins with an introduction to the objectives and expectations, providing a clear roadmap for you. You will explore the concepts of statistical arbitrage and cointegration and understand how to trade the spread based on the Z-score. Dive into the nuances of hedge ratio and half-life and discover how to apply the Kelly Criterion for optimal position sizing and risk management. DYDX FastTrack empowers you to seamlessly configure MetaMask, Alchemy HTTP provider, and access DYDX credentials. Interact with the DYDX API for public price data retrieval and placing orders through the private API. This comprehensive guide includes environment setup in VS Code, Python VENV setup, and creating a collaborative GitHub repository. Master the integration process with environment variables for flawless operations. In the Bot Build stages, you will configure bot constants, construct market prices, and implement cointegration functions. Explore the BotAgent class, which forms the backbone of your trading bot, and effectively manage open trades and exits. Finally, deploy your bot on the AWS cloud, set up real-time Telegram updates, and achieve full automation with CRON. By the end of this course, you will be equipped with the knowledge and skills to develop and deploy an advanced decentralized trading bot on DYDX, leveraging the power of Python and AWS. What You Will Learn Create a statistical arbitrage strategy based on cointegration Implement position sizing and risk management techniques for successful trading Learn how to connect and access DYDX API for trading Understand the concept of z-score and its application in trading spreads Explore Telegram messaging integration for real-time trade notifications Gain proficiency in deploying your bot on AWS for continuous trading Audience This course is ideal for intermediate to advanced Python developers and cryptocurrency enthusiasts aiming to enhance their trading abilities on the DYDX platform. Basic proficiency in Python is required for in-depth coding and bot development. While prior knowledge of cryptocurrency trading strategies is beneficial, it is not mandatory. Access to a computer with internet connectivity is necessary to set up the development environment and interact with DYDX. Familiarity with blockchain technology and decentralized exchanges is recommended for better comprehension. About The Author XCHAIN ANALYTICS LTD: XCHAIN ANALYTICS LTD is a leading analyst and full-stack developer with expertise in Python and React. Their passion lies in discovering and promoting innovative ideas that are often overlooked in the hype-driven tech industry. With a focus on authenticity and practicality, XCHAIN ANALYTICS strives to share their knowledge and empower others through teaching. They believe in the power of continuous learning and experimentation and often find themselves exploring new ventures. However, they always return to teaching as their true calling, where they can put their ideas into action and help others effectively.
    Note: "Published in June 2023.". - Online resource; title from title details screen (O'Reilly, viewed August 7, 2023)
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  • 22
    Online Resource
    Online Resource
    LangChain masterclass : build 15 OpenAI and LLAMA 2 LLM apps using Python (2023)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781835464427 , 1835464424
    Language: English
    Pages: 1 online resource (1 video file (10 hr., 2 min.)) , sound, color.
    Edition: [First edition].
    DDC: 004.6
    Keywords: Artificial intelligence ; Computer programming ; Chatbots ; Application program interfaces (Computer software) ; Python (Computer program language) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Unlock the boundless possibilities of AI and language-based applications with our LangChain Masterclass. In this comprehensive course, you will embark on a transformative journey through the realms of LangChain, Pinecone, OpenAI, and LLAMA 2 LLM, guided by experts in the field. In this course, you will embark on a journey through a diverse range of projects designed to deepen your understanding and application of cutting-edge technologies. These hands-on endeavors encompass a broad spectrum of applications, from creating dynamic question-answering applications powered by LangChain, OpenAI, and Hugging Face Spaces, to developing engaging conversational bots that enhance user interactions. You will even venture into the realm of educational AI, crafting customized experiences for children. As you progress, you will build captivating marketing campaigns, explore the world of summarization-enriched chatbots, and streamline tasks such as multiple-choice quiz creation and CSV data analysis. Plus, you will discover how to optimize HR processes, simplify email customization, and extract vital invoice details. With projects spanning from text-to-SQL query assistance to customer care call summaries, this course equips you with a comprehensive toolkit for advancing your skills and revolutionizing various domains of AI and software development. By the end of this course, you will not only have a strong grasp of LangChain's capabilities but also a robust portfolio of AI applications that showcases your expertise. What You Will Leanr Build AI-powered chatbots and applications with LangChain Create dynamic question-answering systems and conversational bots Implement automated marketing and customer support tools Learn to streamline data analysis and CSV processing Explore HR resume screening and email customization Master invoice data extraction and SQL query tools Audience This course is designed for individuals eager to explore the dynamic world of AI-powered language applications. If you are passionate about harnessing the potential of LangChain, Pinecone, OpenAI, and LLAMA 2 LLM, this course is your gateway to expertise. Prerequisites are minimal, requiring only a basic understanding of programming and coding. A curious mind and enthusiasm for AI are your most valuable assets. About The Author Sharath Raju: Sharath Raju is a senior software engineer specialized in AI and robotics. It has been over eight years since he worked in software development, robotic process automation (RPA), and AI app implementation. He has implemented over 80 RPA processes using UiPath and Microsoft Power Automate and has also built several AI-powered apps using different technologies. It is so true that someone learns more efficiently by practicing the skill than just reading something. Having a passion to share his knowledge in these technologies, he has created several step-by-step and easy-to-digest courses. His goal is to help you get ready for the future by learning new technologies and to prepare you to become more productive by getting familiar with the relevant and useful resources. He is still learning and exploring his field of work, and therefore, he welcomes any valuable feedback.
    Note: "Updated in September 2023.". - Online resource; title from title details screen (O'Reilly, viewed October 11, 2023)
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  • 23
    Online Resource
    Online Resource
    Python 101 : from noob to nerd (2023)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781835465271 , 1835465277
    Language: English
    Pages: 1 online resource (1 video file (7 hr., 25 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Python, one of the most sought-after programming languages, has transformed the landscape of data analytics, application development, and automation. Our course is meticulously structured to guide you through the fundamentals of Python programming. Starting with an introduction to how organizations utilize Python to gain competitive advantages, we delve into the nuances of setting up Python on different operating systems, understanding the syntax, working with different data types, and mastering control flows. As you progress, you'll explore the depths of data structures in Python - lists, tuples, sets, and the all-powerful dictionaries. But that's just scratching the surface. We also introduce you to the world of data processing with Pandas, where you'll get hands-on experience with series, Dataframes, and advanced data manipulation techniques. By the end of this course, not only will you have a strong foundation in Python programming, but you'll also be equipped with the skills to apply these concepts in real-world scenarios, giving you a significant edge in your professional journey. With our course, you're not just learning; you're evolving into a more skilled and confident technical professional. What You Will Learn Dive into Python's role in data analytics and decision-making Write clear, efficient analytics scripts in Python Master handling numeric, text, and Boolean data types in Python Learn the essentials of Python's virtual environments Control code flow using if, elif, and else statements Learn the basics of Pandas, Series, and DataFrames Audience This course is tailor-made for individuals keen on mastering a versatile skill set that transcends multiple coding languages. Whether you're a novice exploring new avenues or a seasoned professional looking to diversify, if you possess a passion for acquiring skills that are highly sought-after in today's tech landscape. About The Authors Mike Meyers: Total Seminars, led by Mike Meyers and his esteemed team of IT pros, boasts over 1 million enrollments and has delivered unparalleled certification training to myriad organizations, including the FBI, UN, and the Department of Defense. Renowned for producing the top-selling CompTIA A+ and Network+ Certification guides, with over a million copies circulating, they have pioneered compelling video courses and supportive materials such as TotalTester practice tests and TotalSims lab simulations, all accessible on their website. Dartanion Williams: Meet Dartanion Williams, an instructor brimming with passion for IT. With a robust 18-year tenure, Dartanion has seamlessly blended curiosity with technical prowess, steering teams towards optimal performance. His accolades span from ushering Chicago's web-based student management to reforming EMS in Washington, D.C. Dartanion's technical arsenal includes SQL, JavaScript, Power BI, Tableau, and mobile app design, underscoring his versatility in the IT realm.
    Note: "Total Seminars.". - Online resource; title from title details screen (O'Reilly, viewed November 15, 2023)
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  • 24
    Online Resource
    Online Resource
    Shiny for Python ultimate : web development with Python (2023)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781805122753 , 1805122754
    Language: English
    Pages: 1 online resource (1 video file (3 hr., 8 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: In the rapidly evolving landscape of web development, harnessing the power of Python to create dynamic and interactive web applications has become essential. This course empowers beginners with the tools to master web development using Python as their primary resource. Beginning with the fundamental building blocks of web development, you will explore Shiny for Python, a package that revolutionizes the creation of user interfaces, widgets, and interactive features. From structuring your app and designing layouts to implementing control widgets and reactivity, you will gain a deep understanding of web application development. The course then delves into hands-on projects, covering a diverse range of topics. You will learn how to fetch user input and create interactive apps, progressing to advanced concepts including climate change visualization with elements such as progress bars, interactive maps, and stylish UI components. Furthermore, the course provides invaluable insights into deployment strategies, including shinylive, GitHub Pages, Web Assembly, GitHub Gist, and Posit Connect, giving your creations a global reach. With practical exercises and real-world projects, this course is the ultimate guide to becoming a proficient Python web developer using Shiny. What You Will Learn Create user-friendly interfaces with control widgets and dynamic reactivity Implement climate change app features, progress bars, and interactive maps Learn deployment techniques such as GitHub Pages, shinylive, and shinyapps.io Understand Web Assembly and its role in deploying Python web applications Explore Posit Connect for seamless and efficient app deployment Develop proficiency in Python-based web app development strategies Audience This course is tailor-made for Python developers eager to venture into the world of web development. Whether you are a beginner seeking to build interactive web applications or an experienced developer looking to expand your skill set, this course is designed for you. No prior web development experience is required, but a basic understanding of Python is recommended to grasp the concepts effectively. About The Author Bert Gollnick: Bert Gollnick is a proficient data scientist with substantial domain knowledge in renewable energies, particularly wind energy. With a rich background in aeronautics and economics, Bert brings a unique perspective to the field. Currently, Bert holds a significant role at a leading wind turbine manufacturer, leveraging his expertise to contribute to innovative solutions. For several years, Bert has been a dedicated instructor, offering comprehensive training in data science and machine learning using R and Python. The core interests of Bert lie at the crossroads of machine learning and data science, reflecting a commitment to advancing these disciplines.
    Note: "Updated September 2023.". - Online resource; title from title details screen (O'Reilly, viewed October 11, 2023)
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  • 25
    Online Resource
    Online Resource
    Python for game programming : Pygame from A to Z (2023)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781835464809 , 1835464807
    Language: English
    Pages: 1 online resource (1 video file (3 hr., 48 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Video games Programming ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Embark on a comprehensive journey into game development with our in-depth course, covering everything from the fundamentals to advanced techniques using Python and the powerful Pygame library. Start by understanding the capabilities of Pygame and learn how to set up a development environment for seamless coding. Explore the artistic side by drawing shapes on a surface and master the intricacies of handling keyboard events and frame rates. As you progress, add depth to your games by implementing boundaries, jump logic, and captivating background images. Gain proficiency in working with sprites, delving into object-oriented programming for efficient game structure. Learn to introduce projectiles, enemies, and collision detection, enhancing the interactive nature of your creations. You will also delve into advanced topics such as scrolling backgrounds, game difficulty levels, and dynamic elements like health bars and scoring systems. The course also provides hands-on experience in addressing common challenges, from fixing bugs to making interactive buttons. By the end, you will not only have a diverse portfolio of 2D games but also a robust skill set in Python and Pygame, positioning you as a proficient game developer ready to bring your creative visions to life. What you will learn Develop a variety of 2D games, including platformers, puzzles, and arcade-style games, from scratch Utilize Pygame's features for graphics, sound effects, and user input to create interactive and engaging gaming experiences Debug and optimize Pygame code for smooth gameplay and performance, handling different game states and events effectively Implement game physics and controls, covering aspects such as collision detection, sprite movement, and character animation in Pygame Manage game state and screen transitions, such as starting, pausing, and ending games, with efficient code structures Learn to deploy completed Pygame applications for wide distribution Audience This course is designed for aspiring game developers, Python programmers seeking skill enhancement, hobbyists eager to craft captivating games, and freelancers or entrepreneurs looking to monetize their creations. Whether you are starting your game development journey or aiming to diversify your skillset, this course provides tailored insights. Tailored to accommodate beginners yet comprehensive enough for intermediate programmers, this course takes you from the foundational principles of game development to creating your own games from scratch. About the Author Meta Brains: Meta Brains is a professional training brand developed by a team of software developers and finance professionals who have a passion for finance, coding, and Excel. They bring together both professional and educational experiences to create world-class training programs accessible to everyone. Currently, they're focused on the next great revolution in computing: The Metaverse. Their ultimate objective is to train the next generation of talent so that we can code and build the metaverse together!.
    Note: Online resource; title from title details screen (O'Reilly, viewed Decenber 5, 2023)
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  • 26
    Online Resource
    Online Resource
    The complete Python course (2022) (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781837636778 , 183763677X
    Language: English
    Pages: 1 online resource (1 video file (5 hr., 13 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Python is a powerful object-oriented programming language used in many development areas and is considered a perfect language for scripting. Python is a cross-platform programming language that allows you to code faster with lesser code writing required. The course begins with a complete introduction to the capabilities and features of Python and how to set up the language on your computer along with PyCharm IDE. You will learn about multiple programming-paradigms (object-oriented, functional, and imperative). You will explore the concepts of an interpreted language that is dynamically typed and cross-platform. The course advances to explain the concepts of OOP: variables, user input, statements, functions, classes, and objects. You will learn about functions, tuples, dictionaries, and lists in Python. You will also explore various operator modules including math, statistics, and random modules. You will work on practical examples to understand the concepts of Python programming well. Upon completion, you will master advanced-level programming skillsets of Python and execute codes successfully. You will be able to complete your quest for learning to program using Python. Using the various built-in Python modules, you will grasp a must-know skill for data science and interpretation. What You Will Learn Learn multiple programming paradigms (OOPs and functional programs) Learn variables, classes, objects, tuples, strings, and operators Use dynamically typed interpreted language for lesser coding lines Create lists, loops, functions, tokens, sets, and dictionaries Understand cross-platform, dynamic, interpreted, and intuitive coding Use random, math, and statistical operators to handle data Audience This course is designed for beginners in programming and those who want to master Python programming skills. Intermediate-level Python programmers who want to enhance their Python Programming Skills and students and Engineers who wish to learn Python as part of their academics. This course would also benefit professional programmers who want to switch to Python Programming from alternative coding platforms. The course only requires the learners to have basic computer knowledge to gain from this course, and no other learning prerequisites are required. About The Author Amit Diwan: Studyopedia was founded by Amit Diwan in 2018 after working for Tutorialspoint , IIT, IASRI, Sitepoint, DU, and C# Corner. Studyopedia sells courses on Udemy, Tutorialspoint, Geeksforgeeks, and Skillshare, providing video courses to master various technologies and programming languages, databases, frameworks, Python, data science, machine learning, Java, Android, C/C++, HTML5, Bootstrap, JavaScript, jQuery, PHP, CSS, WordPress, Drupal, Joomla, Magento, osCommerce, OpenCart, PrestaShop, and other disciplines. Studyopedia delivers high-quality video courses to millions of students and professionals enrolled through their website on multiple programming languages and technologies.
    Note: Online resource; title from title details screen (O'Reilly, viewed January 5, 2023)
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  • 27
    Online Resource
    Online Resource
    Concurrent and parallel programming in Python (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781804611944 , 1804611948
    Language: English
    Pages: 1 online resource (1 video file (6 hr., 9 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Computer programming ; Python (Computer program language) ; Instructional films ; Internet videos ; Nonfiction films ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: In a big data project, a plethora of information is retrieved, big numbers are crunched on our machine, or both. If the coding is sequential or synchronous, our application will struggle to execute. Two mechanisms to alleviate such bottlenecks are concurrency and parallelism. In Python, concurrency is represented by threading, whereas multiprocessing achieves parallelism. This course begins with an introduction about potential programming speed bottlenecks and solving them. You will delve into Python concepts and create a Wikipedia Reader, Yahoo Finance Reader, Queues, and Master Scheduler. You will build a multi-threaded program to grab data from the Internet and parse and save them into a local database. Implement multiprocessing in Python, which lets us use multiple CPUs in our code. Learn about threading, multiprocessing, asynchronous wait, locking, multiprocessing queues, Pool Map Multiple Arguments, writing asynchronous programs, and combining async and multiprocessing. Upon completion, we can spread our workload over all cores available on the used machine. We will combine both elements, multiprocessing with asynchronous programming, to maximize benefit and CPU resource usage and minimize the time spent waiting for IO responses. You will create multi-threaded, asynchronous, multi-process programs to make programs run faster. What You Will Learn Learn to use concurrency and parallelism in Python Write multi-threaded programs in Python to reduce coding lengths Write multi-process programs that execute even faster Understand the differences between concurrency and parallelism Create asynchronous programs in Python by adding concurrency Spread workload over all the cores available on a machine being used Audience This course is aimed at intermediate- to mastery-level seeking programmers, API developers, web developers, and application developers who know basic- to intermediate-level Python coding beforehand. The topics on concurrency and parallelism expect one to be aware of basic to intermediate understanding of coding on Python. Prior knowledge of basic Python coding is desirable for optimal benefit from this course. About The Author Maximilian Schallwig: Maximilian Schallwig is a data engineer and a proficient Python programmer. He holds a bachelor's degree in physics and a master's degree in astrophysics. He has been working on data for over five years, first as a data scientist and then as a data engineer. He can talk endlessly about big data pipelines, data infrastructure, and his unwavering devotion to Python. Even after two unsuccessful attempts in high school, he still decided to learn Python at the University. He cautiously stepped into the realm of data, beginning with a simple Google search for "what does a data scientist do" He was determined to pursue a career in data science to become a data engineer by learning about big data tools and infrastructure design to build scalable systems and pipelines. He enjoys sharing his programming skills with the rest of the world.
    Note: "Published in November 2022.". - Online resource; title from title details screen (O'Reilly, viewed November 28, 2022)
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  • 28
    Online Resource
    Online Resource
    Web scraping tutorial with Scrapy and Python for beginners (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781804615317 , 1804615315
    Language: English
    Pages: 1 online resource (1 video file (7 hr., 39 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Data mining ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Web scraping is the process of scraping websites and extracting desired data from them, and in this course, you will learn and master web scraping using Python and Scrapy with a step-by-step and in-depth guide. The course starts with introducing you to the web scraping process (with infographics--no code); learn how to scrape data from websites and how to use Scrapy for this. After getting the basics clear, you will perform web scraping using Python and the Scrapy framework! After you have built an actual web scraper, you will get an idea of how web scraping works first-hand. You will then look at the essential concepts of web scraping and Scrapy. Learning how to scrape websites and the essentials already makes you a complete web scraper but you will take this even further and learn the advanced web scraping techniques to become an expert. Advanced topics such as crawling multiple pages and extracting data--pagination, scraping data using Regular Expressions (RegEx), scraping dynamic or JavaScript-rendered websites using Scrapy Playwright--will be thoroughly explained. Finally, you will perform three projects at the end--Champions League Table [ESPN], Product Tracker [Amazon], and Scraper Application [GUI]. By the end of this course, you will have learned how to do web scraping using Python and Scrapy. What You Will Learn Send a request to a URL to scrape websites using Scrapy Spider Get the HTML Response from the URL and parse it for web scraping Use Scrapy shell commands to test and verify CSS Selectors or XPath Export and save scraped data to online databases such as MongoDB Scrape data from multiple web pages using Scrapy pagination Login to websites using Scrapy FormRequest with CSRF tokens Audience This course is ideal for beginner Python developers who want to master web scraping or freelance web scrapers looking to polish their skills. Any individual and college students working on their projects and wanting to master web scraping using Python and the Scrapy module, then this course is for you. A basic understanding of Python programming is a must and elementary-level knowledge of HTML basics will be a plus but not mandatory. About The Author Rahul Mula: Rahul Mula is a developer specializing in Python, Flutter, and web development. He was really intrigued the first time he learned about programming and realized what could be done with it. He loves to explore different technologies and create applications to build something new. He has developed Keyviz--the free and open-source tool to visualize keystrokes in real-time. He has written books and created courses on Python programming teaching thousands of students.
    Note: "Published in November 2022.". - Online resource; title from title details screen (O'Reilly, viewed December 12, 2022)
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  • 29
    Online Resource
    Online Resource
    Python for Software Engineering Bootcamp (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781804617205 , 1804617202
    Language: English
    Pages: 1 online resource (1 video file (41 hr., 8 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. This hands-on course will help you become a skilled software engineer with no prior programming experience needed. You will start by learning the basics of Python such as variables, strings, Booleans, lists, tuples, dictionaries, generators, and so on as well as learning to write the first service test. Furthermore, you will learn to send requests in Python and understand how to modify permissions. You will also be able to explore Docker and SQL and learn to set up a local PostgreSQL Server. You will learn how to create tables using query results. Moving further in the course, you will learn to integrate databases into your application and create database models in Python. You will be introduced to Redis and learn data compression. You will also get to know how to set up a GitHub desktop, and clone a repository as well as GitHub CLI. You will wrap up the course by having a look at threading in Python, multiprocessing pool, and async wait statements. By the end of this course, you will feel comfortable with developing applications, have a portfolio item, and be ready to apply for software engineer positions and take on those technical interviews. What You Will Learn Learn to write proper and clean Python code Learn to develop APIs in Python Learn to write scalable applications in Python Learn to interact with databases in code Learn to add caching to your code Learn to properly test your code Audience This course is for complete beginners who want to learn how to program and become software engineers. No prior programming experience is needed, you will learn everything you will need to know on the course. About The Author Maximilian Schallwig: Maximilian Schallwig is a data engineer and a proficient Python programmer. He holds a bachelor's degree in physics and a master's degree in astrophysics. He has been working on data for over five years, first as a data scientist and then as a data engineer. He can talk endlessly about big data pipelines, data infrastructure, and his unwavering devotion to Python. Even after two unsuccessful attempts in high school, he still decided to learn Python at the University. He cautiously stepped into the realm of data, beginning with a simple Google search for "what does a data scientist do" He was determined to pursue a career in data science to become a data engineer by learning about big data tools and infrastructure design to build scalable systems and pipelines. He enjoys sharing his programming skills with the rest of the world.
    Note: "Published in November 2022.". - Online resource; title from title details screen (O'Reilly, viewed December 12, 2022)
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  • 30
    Online Resource
    Online Resource
    PEP8 guidelines : Python clean coding (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781837632107 , 1837632103
    Language: English
    Pages: 1 online resource (1 video file (5 hr., 4 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer software Development ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: The PEP 8 document provides guidelines and best practices on how to write Python code. If you follow PEP 8, you can be sure that you have named your variables well. You will know that you have added enough whitespace so it's easier to follow logical steps in your code. You will also have commented on your code well. All this will mean your code is more readable and easier to come back to. As a beginner, following the rules of PEP 8 can make learning Python a much more pleasant task. We will start by installing Python and PyCharm on our systems followed by understanding the basics of Python. We will cover core concepts such as objects and data types. You will learn to take inputs from the user, and understand arithmetic and logical operations as well as loops in Python. You will learn about PEP8 code layout as well as PEP 8 imports and dunder names. You will also understand string quotes, whitespace in functions, and logical operation. Lastly, you will learn about programming recommendations and create two practice projects to help you get familiar with the topics covered. By the end of the course, you will be able to develop full-scale professional Python projects. What You Will Learn Learn the best clean code practices in Python Develop full scale professional Python projects Write Python code that conforms to PEP 8 Learn about exceptions, global and local variables Learn about arithmetic and logical operations Audience This course can be taken by Software Engineers that wish to improve their coding efficiency. It can also be taken by computer science students that want to code professionally and anyone with a desire to learn Python and PEP8. A basic understanding of any programming language is needed. About The Author Martin Yanev: Martin Yanev is an internationally acclaimed aerospace software engineer. He holds a bachelor's degree in aeronautical engineering and a master's degree in aerospace dynamics. He is an associate member of the Royal Aeronautical Society in the United Kingdom and is ISTQB certified with solid experience in systems test and integration. He became adept at programming skills in the past seven years by developing and testing complex software algorithms for aerospace applications. He is currently involved in the Single European Sky Project, which aims to increase the European airspace capacity by applying cutting-edge air traffic management systems.
    Note: "Published in November 2022.". - Online resource; title from title details screen (O'Reilly, viewed December 12, 2022)
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  • 31
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    Online Resource
    The art of doing : Python network applications with sockets (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781837631599 , 183763159X
    Language: English
    Pages: 1 online resource (1 video file (14 hr., 34 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Application software Development ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: In this course, you will learn how to set up your own home network with static IP addresses and port forwarding so that anyone can access your programs over the Internet. Then you will learn how to set up a simple two-way chat in the terminal using the Socket module. Next, you will learn how to use the threading module to create a simple chat room in the terminal and how to use the Tkinter module to create a GUI chat room like the old AOL chat rooms. Later, we will look at how to create an advanced GUI chat room with admin window using the JSON module, and finally, how to create your own online multiplayer game using the Pygame module. As this is a project-based course, each project builds on the knowledge gained during the previous projects. In our culminating project, when we attempt to create our own online multiplayer game, we will be generating IPV4/TCP sockets to connect computers to a server running on a machine with a static IP and port forwarding enabled, creating various threads to run processes concurrently on our machines, we will use JSON to serialize python objects such as our game state and game players, and have a fully interactive GUI interface using Pygame. By the end of this course, you will have multiple projects you can share with friends or family, have them run a client script from their house, connect to your server script, and show off all you learned. What You Will Learn Use the socket module to create a terminal-based two-way chat Use the threading module to create a terminal-based chat room Use a Tkinter module to make a GUI chat room Configure router to allow communication from an external network Use the JSON/Pickle modules to build an advanced GUI chat room with an admin window Use the Pygame module to create an online multiplayer game Audience This intermediate course is intended for students with a basic understanding of Python and core programming concepts as well as comfort levels with both functional and object-oriented programming, as both will be used in the course's second half. Also, who is interested in learning how to write programs that can work over a network and communicate with one another. Although it will be helpful to have prior knowledge of different Python modules, we will take the time to teach you everything you need to know to construct the program in this course. About The Author Michael Eramo: Michael Eramo is a life-long learner, a self-taught programmer, and an experienced educator. He holds official bachelor's degrees in music, education, and physics and a master's in mathematics. He is also a Microsoft certified software developer. He has years of experience as a high school physics teacher, computer science teacher, and college mathematics teacher. He is a part of the New York State Master-Teacher Program, a network of more than 800 outstanding public-school teachers throughout the state who share a passion for STEM learning and for collaborating with colleagues to inspire the next generation of STEM leaders.
    Note: "Published in November 2022.". - Online resource; title from title details screen (O'Reilly, viewed December 12, 2022)
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  • 32
    Online Resource
    Online Resource
    Python bootcamp in a day : Python programming for beginners (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781837630400 , 1837630402
    Language: English
    Pages: 1 online resource (1 video file (3 hr., 43 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Python is one of the most popular computer programming languages and this hands-on course for beginners will make it easy for someone who wants to get started with learning Python. This course takes you through the introduction to the course and the learning objectives. You will learn to get started with Replit and write your first Python program. You will learn to store, process, and compare information in Python as well as learn to tidy messy data. You will learn about variables, strings, dictionaries, indexing, and slicing in Python. Further, you will understand loops in Python along with break, continue, and else functions. Moving ahead, you will understand error handling in Python, get to know the try-and-catch block, and learn to add resources to Replit. You will also understand function parameters and explore the difference between local and global variables, and positional and keyword parameters. You will learn to work with JSON and clean the data along with various numeric functions such as min, max, and sum. By the end of the course, you will gain a solid foundation in Python programming and be able to write high-quality code in Python. What You Will Learn Master Python programming fundamentals Learn how to install Python to get up and running in no time Learn how to process data to create Olympics Medals Tables Solve multiple specific problems for a customer in the real world Learn all about objects and variables in Python Understand functions and function parameters in Python Audience Whether you are a software engineer, software developer, computer programmer, web developer, transitioning into a new role, or simply someone who wants to understand what makes Python tick, this is the place to start. If you are preparing for a Python certification or job role, this course is for you. About The Author Paul Ashun: Paul Ashun is the CEO, MD, and chief consultant at Pashun Consulting Ltd., specializing in Scrum coaching and leadership within major global organizations. They are the authors of over 10 books on Scrum such as The Power of Scrum in the Real World, Confessions of a Scrum Master as well as the upcoming Agile User Storybook. He started as a software developer and over ten years later, he became an Agile portfolio manager. He is a certified Scrum Master and a PMO manager. He has led projects for the BBC, General Electric, Oracle, BSkyB, HiT Entertainment, and Razorfish. He has been coaching product owners and business analysts in international blue-chip companies dating back to 1999, in Agile and Scrum practices such as writing user stories.
    Note: "Published in December 2022.". - Online resource; title from title details screen (O'Reilly, viewed January 10, 2023)
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  • 33
    Online Resource
    Online Resource
    Data manipulation in Python : master Python, NumPy, and Pandas (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781804614396 , 1804614394
    Language: English
    Pages: 1 online resource (1 video file (3 hr., 49 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.133
    Keywords: Python (Computer program language) ; Electronic data processing ; Programming languages (Electronic computers) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Master important data manipulation techniques for data science in Python by learning Python, NumPy, and Pandas About This Video Discover the basics of Python programming The most important Python libraries for data science Learn how to use Python to clean, visualize, and analyze data In Detail Data science is quickly becoming one of the most promising careers in the twenty-first century. It is automated, program-driven, and analytical. As a result, it's no surprise that the demand for data scientists has been expanding in the job market over the last few years. We will begin with a quick refresher on Python fundamentals for beginners in this course. This is optional; if you're already familiar with Python, skip to the next chapter. Data science will be the topic of the next three sections. We will start with the essential Python libraries for data science, then go on to the fundamental NumPy properties, and lastly begin with mathematics and how to use it in data science. You will learn about Python Pandas DataFrames and series after learning about data science. Following that, we will get down to business and begin data cleaning. Following that, we will learn how to use Python to visualize data and do data analysis on some sample datasets. Finally, we will cover the Time series in Python and learn how to work with and convert datasets to Time series. By the end of this course, you will be able to execute data manipulation for data science in Python with ease. Audience This course is open to students of all skill levels, and you will be able to succeed even if you have no prior programming or statistical knowledge.
    Note: "Updated in May 2022.". - "Meta Brains.". - Online resource; title from title details screen (O'Reilly, viewed June 6, 2022)
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  • 34
    Online Resource
    Online Resource
    Python for machine learning : the complete beginner's course (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781804619308 , 1804619302
    Language: English
    Pages: 1 online resource (1 video file (2 hr., 29 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3/1
    Keywords: Machine learning ; Python (Computer program language) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Learn Python programming and Scikit-Learn applied to machine learning regression in this comprehensive guide for beginners About This Video Learn how to use different frameworks in Python to solve real-world problems using deep learning and artificial intelligence Build artificial neural networks with TensorFlow and Keras Make predictions using linear regression, polynomial regression, and multivariate regression In Detail Machine learning is a branch of computer science in which you can use mathematical input to develop complicated models that fulfil various roles. Python is a popular choice for building machine learning models because of the large number of libraries available. This course will walk you through an astonishing combination of Python and machine learning, teaching you the fundamentals of machine learning so you can construct your own projects. We will begin by studying Python programming and applying Scikit-Learn to machine learning regression in this course. After that, we will look at the theory underpinning simple and multiple linear regression algorithms. Following that, we will look at how to solve linear and logistic regression issues. Later, we will use sklearn to learn both the theory and the actual application of logistic regression. We will also go into the math underpinning decision trees. Finally, you will learn about the various clustering algorithms. By the end of this course, you will be able to use these algorithms in the real world. Audience This course is for anyone interested in pursuing a career in machine learning, as well as Python programmers who want to add machine learning skills to their resume. This course will also benefit technologists who want to learn more about how machine learning works in the real world. This course requires familiarity with the fundamentals of Python, as well as readiness, flexibility, a will to learn, and, most importantly, basic mathematical skills.
    Note: "Published in September 2022.". - Online resource; title from title details screen (O'Reilly, viewed October 4, 2022)
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  • 35
    Online Resource
    Online Resource
    Practical data science using Python (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781804611814 , 1804611816
    Language: English
    Pages: 1 online resource (1 video file (29 hr., 48 min.)) , sound, color.
    Edition: [First edition].
    DDC: 004.4/22
    Keywords: Quantitative research ; Python (Computer program language) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Explore data science using Python, statistical techniques, EDA, NumPy, Pandas, Scikit Learn, and Statsmodel libraries and take your first step toward becoming a data scientist or a machine learning engineer. About This Video Detailed coverage of Python for data science and machine learning Learn about model optimization using hyperparameter tuning Learn about unsupervised learning using K-Means clustering In Detail In this course, you will learn about core concepts of data science, exploratory data analysis, statistical methods, role of data, Python language, challenges of bias, variance and overfitting, choosing the right performance metrics, model evaluation techniques, model optimization using hyperparameter tuning and grid search cross validation techniques, and more. You will learn how to perform detailed data analysis using Python, statistical techniques, and exploratory data analysis, using various predictive modeling techniques such as a range of classification algorithms, regression models, and clustering models. You will learn the scenarios and use cases of deploying predictive models. This course also covers classification using decision trees, which include the Gini index and entropy measures and hyperparameter tuning. It covers the use of NumPy and Pandas libraries extensively for teaching exploratory data analysis. In addition, you will also explore advanced classification techniques and support vector machine predictions. There is also an introductory lesson included on Deep Neural Networks with a worked-out example on image classification using TensorFlow and Keras. By the end of the course, you will learn some basic foundations of data science using Python. Audience This course is for Python, machine learning developers, data scientists, data analysts, and business analysts. This course will also be beneficial for aspiring data science professionals and machine learning engineers. Exposure to programming languages will be useful.
    Note: "Updated in August 2022.". - Online resource; title from title details screen (O'Reilly, viewed September 13, 2022)
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  • 36
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    Online Resource
    Python for deep learning : build neural networks in Python (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781804617878 , 1804617873
    Language: English
    Pages: 1 online resource (1 video file (2 hr., 9 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3/1
    Keywords: Deep learning (Machine learning) ; Python (Computer program language) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Master Data Science, TensorFlow, Artificial Intelligence, and Neural Networks with this comprehensive deep learning course for absolute beginners About This Video Fundamentals course designed for both beginners and experts alike Use different frameworks in Python to solve real-world problems using deep learning and AI Make predictions using linear regression, polynomial regression, and multivariate regression In Detail Python is famed as one of the best programming languages for its flexibility. It works in almost all fields, from web development to developing financial applications. However, it's no secret that Python's best application is in deep learning and artificial intelligence tasks. We will start with an introduction to deep learning where we will focus on the fundamentals of the deep learning theory and learn how to use deep learning in Python. Followed by this we will move on to Artificial Neural Networks (ANN). You will learn how to use different frameworks in Python to solve real-world problems using deep learning and artificial intelligence. Next, we will make predictions using linear regression, polynomial regression, and multivariate regression, and build artificial neural networks with TensorFlow and Keras. We will also cover Convolutional Neural Networks (CNN) at length and go through the different components such as convolution layer, pooling layer, and fully connected layer. Finally, we will wrap up the implementation of CNN in Python. By the end of this course, you will be able to use the concepts of deep learning to build neural networks in python like a professional. Audience This course is intended for both beginners and professionals in programming who want to expand their knowledge of deep learning or professional mathematicians who want to learn how to analyze data programmatically. Basic mathematical skills and Python coding experience are prerequisites.
    Note: Online resource; title from title details screen (O'Reilly, viewed September 13, 2022)
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  • 37
    Online Resource
    Online Resource
    Reinforcement learning and deep RL Python (theory and projects) (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781804610626 , 1804610623
    Language: English
    Pages: 1 online resource (1 video file (14 hr., 18 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.31
    Keywords: Reinforcement learning ; Python (Computer program language) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: A comprehensive, hands-on, and easy-to-understand course on reinforcement learning. Learn about deep Q-Learning, SARSA, deep RL, car racing and trading projects, and be prepared with interview questions. About This Video Learn from a comprehensive yet self-explanatory course, divided into 145+ videos along with detailed code notebooks Structured course with solid basic understanding and advanced practical concepts Up-to-date, practical explanations and live coding with Python to build six projects at an adequate pace In Detail Reinforcement learning is a subset of machine learning. In the RL training method, desired actions are rewarded, and undesired actions are punished. Deep RL is also a subfield of machine learning. In deep RL, intelligent machines and software are trained to learn from their actions in the same way that humans learn from experience. Deep RL has the capability to solve complex problems that were unmanageable by machines in the past. Therefore, the potential applications of deep RL in various sectors are enormous. We will start with an introduction to reinforcement learning and look at some case studies and real-world examples. Then you will look at Naïve/Random solutions and RL-based solutions. Next, you will see different types of RL solutions such as hyperparameters, Markov Decision Process, Q-Learning, and SARSA followed by a mini project on Frozen Lake. You will then learn deep learning/neural networks and deep RL/deep Q networks. Next, you will work on car racing and trading projects. Finally, you will go through some interview questions. By the end of this course, you will be able to relate the concepts and practical applications of reinforcement and deep reinforcement learning with real-world problems and implement any project that requires reinforcement and deep reinforcement learning knowledge from scratch. Audience This course is designed for beginners who know absolutely nothing about reinforcement and deep reinforcement learning, the ones who want to develop intelligent solutions, and the ones who want to learn the theoretical concepts first before implementing them using Python. An individual who wants to learn PySpark along with its implementation in realistic projects, machine learning or deep learning lovers, and anyone interested in artificial intelligence will be highly benefitted. You would need prior knowledge of Python, an elementary understanding of programming, and a willingness to learn and practice.
    Note: "Published in September 2022.". - "AI Sciences.". - Online resource; title from title details screen (O'Reilly, viewed October 4, 2022)
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  • 38
    Online Resource
    Online Resource
    PyCharm productivity and debugging techniques (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781837632442 , 1837632448
    Language: English
    Pages: 1 online resource (1 video file (9 hr., 53 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: PyCharm is a dedicated Python Integrated Development Environment (IDE) providing a wide range of essential tools for Python developers, tightly integrated to create a convenient environment for productive web and data science development. The course covers the following sections: Section 1 is about the introduction and helpful notes for the course. Section 2 discusses the process of managing and customizing your PyCharm workspace. In section 3, you will look at editing and formatting with ease in PyCharm, which offers a detailed view of how PyCharm supports the process of developing Python applications. In Section 4, you will look at version control with Git in PyCharm, including a theoretical discussion about what version control is and why it is important. Section 5 focuses on the use of PyCharm to streamline processes in programming such as testing, debugging, and profiling. In the next section, you will look at web development with JavaScript, HTML, and CSS. In the final section of the course, you will understand Integrating Django in PyCharm, which introduces Django, the premier web development framework in Python. By the end of the course, you will have learned everything about PyCharm productivity and debugging techniques. What You Will Learn Customize PyCharm Theme and Editor Install and manage Python packages with PyCharm Code refactoring and renaming Build PyCharm documentation Learn the process of converting and exporting functions Explore Git version control built-in PyCharm Audience This course is for back-end software engineers and front-end developers. It can also be taken by computer science students and everyone who wants to learn to program. No prior knowledge of Python is required, only a desire to learn PyCharm IDE. About The Author Martin Yanev: Martin Yanev is an internationally acclaimed aerospace software engineer. He holds a bachelor's degree in aeronautical engineering and a master's degree in aerospace dynamics. He is an associate member of the Royal Aeronautical Society in the United Kingdom. He is ISTQB certified with solid experience in systems test and integration. He became adept at programming skills in the past seven years by developing and testing complex software algorithms for aerospace applications. He is currently involved in the Single European Sky Project, which aims to increase the European airspace capacity by applying cutting-edge air traffic management systems.
    Note: Published in October 2022. - Online resource; title from title details screen (O'Reilly, viewed November 8, 2022)
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  • 39
    Online Resource
    Online Resource
    Data science, analytics, and AI for business and the real world™ (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    Language: English
    Pages: 1 online resource (1 video file (30 hr., 55 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.7
    Keywords: Application software Development ; Python (Computer program language) ; SPARK (Computer program language) ; Artificial intelligence ; Artificial Intelligence ; Logiciels d'application ; Développement ; Python (Langage de programmation) ; Intelligence artificielle ; artificial intelligence ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet ; Webcast
    Abstract: Learn to use data science and statistics to solve business problems and gain insights into everyday problems with 35+ case studies About This Video Explore 16 statistical and data analysis, and six predictive modeling and classifiers case studies Work on four: data science in marketing and retail, and two time-series forecasting case studies Dive into three Natural Language Processing and one PySpark big data case studies, and a deployment project In Detail Right now, despite the Covid-19 economic contraction, traditional businesses are hiring data scientists in droves! Therefore, data scientist has become the top job in the U.S. for the last four years running. However, data science has a difficult learning curve. This course seeks to fill all those gaps and has a comprehensive syllabus that tackles all the major components of data science knowledge. You will be using data science to solve common business problems throughout this course. You will start with the basics of Python, Pandas, Scikit-learn, NumPy, Keras, Prophet, statsmod, SciPy, and more. You will learn statistics and probability for data science in detail. Then, you will learn visualization theory for data science and analytics using Seaborn, Matplotlib, and Plotly. You will look at dashboard design using Google Data Studio along with machine learning and deep learning theory/tools. Then, you will be solving problems using predictive modeling, classification, and deep learning. After this, you will move your focus to data analysis and statistical case studies, data science in marketing, and data science in retail. Finally, you will see deployment to the cloud using Heroku to build a machine learning API. By the end of this course, you will learn all the major components of data science and gain the confidence to enter the world of data science. Audience This course is designed for beginners in data science; business analysts who wish to do more with their data; college graduates who lack real-world experience; business-oriented persons who would like to use data to enhance their business; software developers or engineers who would like to start learning data science. Anyone looking to become more employable as a data scientist and with an interest in using data to solve real-world problems will enjoy this course thoroughly. No need to be a programming or math whiz; basic high school math will be sufficient.
    Note: "Updated in March 2022.". - Online resource; title from title details screen (O'Reilly, viewed March 30, 2022)
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  • 40
    Online Resource
    Online Resource
    Data science 101 : methodology, Python, and essential math (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781803242125 , 1803242124
    Language: English
    Pages: 1 online resource (1 video file (14 hr., 51 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.74
    Keywords: Databases ; Computer science ; Python (Computer program language) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: From data science methodology to an introduction to data science in Python, to essential math for data science About This Video Explain data science methodology, starting with business understanding and ending at deployment Identify the various elements of ML and NLP involved in building a simple chatbot Indicate how to create and work with variables, data structures, looping structures, and more In Detail The opening part of Data Science 101 examines some frequently asked questions. Following that, we will explore data science methodology with a case study. You will see the typical data science steps and techniques utilized by data professionals. Next, you will build a simple chatbot so you can get a clear sense of what is involved. The next part is an introduction to data science in Python. You will have an opportunity to master Python for data science as each section is followed by an assignment to practice your skills. By the end of the section, you will understand Python fundamentals, decision and looping structures, Python functions, how to work with nested data, and list comprehension. Finally, we will wrap up the two most popular libraries for data science--NumPy and Pandas. The last part delves into essential math for data science. You will get the hang of linear algebra along with probability and statistics. Our goal for the linear algebra part is to introduce all necessary concepts and intuition for an in-depth understanding of an often-utilized technique for data fitting called least squares. We will spend a lot of time on probability, both classical and Bayesian, as reasoning about problems is a much more difficult aspect than simply running statistics. By the end of this course, you will understand data science methodology and how to use essential math in your real projects. Audience This course is designed for people who are new to data science or who are interested in pursuing a career in data science, as well as those who wish to obtain a broad overview before diving into specialized data science topics. This course will also benefit students who want to master the fundamental arithmetic for data science or obtain an introduction to data science in Python. You need not have any prior experience in data science to take up this course.
    Note: "Updated in April 2022.". - Online resource; title from title details screen (O'Reilly, viewed May 10, 2022)
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  • 41
    Online Resource
    Online Resource
    Django crash course with examples (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781804613962 , 1804613967
    Language: English
    Pages: 1 online resource (1 video file (3 hr., 51 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.2/76
    Keywords: Django (Electronic resource) ; Web site development ; Python (Computer program language) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: A comprehensive course for those who know Python basics and want to be able to build web apps using Python About This Video Learn the different components of the Django web framework using real-world examples Learn and test for yourself and understand how every component behaves by running them on your browser Understand and apply the communication between Django and the SQL database In Detail The course teaching approach is learn-by-doing. You will learn to build two different apps: a modern Bootstrap blog website with a complete blog author interface and a dynamic Google Translate-like translator web app. The two apps have been chosen carefully to cover all core Django features. The apps are also extendible, allowing you to improve and add features to the apps while sharpening your Django skills and building your own GitHub portfolio. Among other topics, you will learn the model-view-template app structure of Django. You will also learn to set up SQL databases and connect the database with your app. You will learn to build complete web pages equipped with HTML widgets and create HTML forms that handle GET and POST HTTP requests. In addition, you will learn how to create and manage URL patterns for your app pages. You will also learn how to build an admin interface, which is useful when building content websites such as blogs, where content creators and other admins can use the admin interface to add content to the website without interfering with the codebase. You will also get an introduction to HTML and learn to create front-end widgets such as input boxes, buttons, and HTML forms. You will learn to give your web app a modern look by adding Bootstrap styling to your website. By the end of the course, you will have all the skills to build your own web apps using Django, and you will know where to look whenever you need to add new Django features to your apps. Audience The course is beneficial for those who want to turn their ideas into web apps. You will be able to create your own web apps in no time. You will also be able to start your web development career with this course. Finally, the program assumes you know Python basics already. If you know Python basics, you can understand and use the Django codebase to build web applications, and this course will take you step-by-step through that process.
    Note: "Updated in July, 2022.". - "PythonHow.". - Online resource; title from title details screen (O'Reilly, viewed July 25, 2022)
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  • 42
    Online Resource
    Online Resource
    Deep learning CNN : convolutional neural networks with Python (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781803243726 , 1803243724
    Language: English
    Pages: 1 online resource (1 video file (15 hr., 28 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3/1
    Keywords: Deep learning (Machine learning) ; Python (Computer program language) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Learn Convolution Neural Networks using TensorFlow, CNN for Image Recognition, and CNN for Object Detection. Understand the concepts and methodologies of CNNs with respect to data science with live coding throughout. About This Video Learn from easy-to-understand, exhaustive, expressive, 75+ videos along with detailed code notebooks Structured course with solid basic understanding and moving ahead with the advanced practical concepts Practical explanation and live coding with Python to build your own application In Detail Convolutional Neural Networks (CNNs) are considered game-changers in the field of computer vision, particularly after AlexNet in 2012. They are everywhere now, ranging from audio processing to more advanced reinforcement learning. So, the understanding of CNNs becomes almost inevitable in all fields of data science. With this course, you can take your career to the next level with an expert grip on the concepts and implementations of CNNs in data science. The course starts with introducing and jotting down the importance of Convolutional Neural Networks (CNNs) in data science. You will then look at some classical computer vision techniques such as image processing and object detection. It will be followed by deep neural networks with topics such as perceptron and multi-layered perceptron. Then, you will move ahead with learning in-depth about CNNs. You will first look at the architecture of a CNN, then gradient descent in CNN, get introduced to TensorFlow, classical CNNs, transfer learning, and a case study with YOLO. Finally, you will work on two projects: Neural Style Transfer (using TensorFlow-hub) and Face Verification (using VGGFace2). By the end of this course, you will have understood the methodology of CNNs with data science using real datasets. Apart from this, you will easily be able to relate the concepts and theories in computer vision with CNNs. Audience This course is designed for beginners in data science and deep learning. Any individual who wants to learn CNNs with real datasets in data science, learn CNNs along with its implementation in realistic projects, and master their data speak will gain a lot from this course. No prior knowledge is needed. You start from the basics and slowly build your knowledge of the subject. A willingness to learn and practice is just the prerequisite for this course.
    Note: "Updated in August 2022.". - Online resource; title from title details screen (O'Reilly, viewed September 13, 2022)
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  • 43
    Online Resource
    Online Resource
    Real-time stream processing using Apache Spark 3 for Python developers (2022)
    [Birmingham, United Kingdom] : Packt Publishing
    Details
    Language: English
    Pages: 1 online resource (1 video file (4 hr., 36 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Spark (Electronic resource : Apache Software Foundation) ; Scala (Computer program language) ; Python (Computer program language) ; Electronic data processing ; Machine learning ; Scala (Langage de programmation) ; Python (Langage de programmation) ; Apprentissage automatique ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet ; Webcast
    Abstract: Build your own real-time stream processing applications using Apache Spark 3.x and PySpark About This Video Learn real-time stream processing concepts Understand Spark structured streaming APIs and architecture Work with file streams, Kafka source, and integrating Spark with Kafka In Detail Take your first steps towards discovering, learning, and using Apache Spark 3.0. We will be taking a live coding approach in this carefully structured course and explaining all the core concepts needed along the way. In this course, we will understand the real-time stream processing concepts, Spark structured streaming APIs, and architecture. We will work with file streams, Kafka source, and integrating Spark with Kafka. Next, we will learn about state-less and state-full streaming transformations. Then cover windowing aggregates using Spark stream. Next, we will cover watermarking and state cleanup. After that, we will cover streaming joins and aggregation, handling memory problems with streaming joins. Finally, learn to create arbitrary streaming sinks. By the end of this course, you will be able to create real-time stream processing applications using Apache Spark. Audience This course is designed for software engineers and architects who are willing to design and develop big data engineering projects using Apache Spark. It is also designed for programmers and developers who are aspiring to grow and learn data engineering using Apache Spark. For this course, you need to know Spark fundamentals and should be exposed to Spark Dataframe APIs. Also, you should know Kafka fundamentals and have a working knowledge of Apache Kafka. One should also have programming knowledge of Python programming.
    Note: Online resource; title from title details screen (O’Reilly, viewed March 10, 2022)
    URL: lizenzpflichtig
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  • 44
    Online Resource
    Online Resource
    Data analytics using Python visualizations (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781804614839 , 1804614831
    Language: English
    Pages: 1 online resource (1 video file (6 hr., 28 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.133
    Keywords: Computer science ; Python (Computer program language) ; Electronic data processing ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Master data science, ML, and analytics with powerful visualizations using Matplotlib, Seaborn, and Bokeh. About This Video The art of presenting data in the form of powerful, innovative, and intuitive visualizations In-depth coverage of Matplotlib, Seaborn, and Bokeh visualization libraries Use of data analytics techniques/Exploratory Data Analysis (EDA) using several data generations and manipulation methods In Detail If you are working on machine learning projects and want to find patterns and insights from your data on your way to building models, then this course is for you. This course takes a holistic approach to teach visualization techniques. We will be taking real-life business scenarios and raw data to go through detailed Exploratory Data Analysis (EDA) techniques to prepare the raw data to suit the appropriate visualization needs. You will learn about data analytics and exploratory data analysis techniques using multiple different data structures with NumPy and Pandas libraries. You will also learn various chart/graph types, customization/configuration, and vectorization techniques. We will look at advanced visualizations using business applications such as single and multiple bar charts, pie charts, and bubble charts with the vectorization of properties. We will further explore Seaborn Boxplot, Violin plot, Categorical Scatterplot, and how to create heat maps. By the end of the course, you will learn the foundational techniques of data analytics and deeper customizations on visualizations. You will be able to confidently use Python visualization libraries such as Matplotlib, Seaborn, and Bokeh in your future projects.\ Audience This course is for Python and machine learning developers, data scientists, data analysts, and business analysts. This course will also be beneficial to leaders, managers, and anyone whose job involves presenting data in the form of visuals, which include developers, architects, and system analysts. A basic understanding of Python will be helpful, but not mandatory.
    Note: "Updated in June 2022.". - Online resource; title from title details screen (O'Reilly, viewed July 6, 2022)
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  • 45
    Online Resource
    Online Resource
    Pandas for beginners : a quick guide (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781804612088 , 1804612081
    Language: English
    Pages: 1 online resource (1 video file (1 hr., 57 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.1
    Keywords: Application program interfaces (Computer software) ; Python (Computer program language) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: If you work in any functional areas of data analysis, machine learning, and artificial intelligence, you will want to be familiar with or master Pandas. Pandas is a popular Python library used for data analysis and manipulation, commonly used with data analysis, artificial intelligence, and machine learning. Pandas enables quick and efficient data manipulation, aggregation, pivoting, and flexible time series. This course will introduce you to the basics of data analysis using the Pandas library. You will learn to work with two primary data structures in Pandas, Series and Data Frame. Then, we will take a look at how to read data from a file and explore input data using indexing and filtering, at which point you will be ready for data preprocessing. Next, we will focus on handling missing values and duplicate rows and transforming data into a more efficient format. You will also discover how to manipulate data and data processing. Finally, we will dive into creating simple plots to visualize the data. By the end of this course, you can use OOPs paradigm to create class hierarchies with the OOP design process. You can design and implement Python programs for complex issues and make good use of the features like classes and inheritance. What You Will Learn Learn basic data analysis with Pandas' open-source Python library Use the two primary Pandas data structures, Series and DataFrame Process varied data types and manipulate data with string function Organize input with index and filter, preprocess data with Pandas Format and process different kinds of data most efficiently Manipulate, aggregate, and pivot data flexibly and efficiently Audience This course targets beginner Python developers or those who want to learn and use the Pandas library for Python. Data analysts, project management analysts, and those working in artificial intelligence, machine learning, or data science can benefit from this course immensely. For those managers and executives that handle a lot of data and create analytic reporting material, this course could help them as well in their data science projects. This course assumes no previous experience in Pandas, but a fundamental understanding of basic Python syntax is needed since it is built for Python. About the Author Simon Sez IT: Simon Sez IT has offered technical courses since 2008 for individuals, small businesses, and Fortune 500 companies with thousands of employees who can benefit from the easy-to-learn and hands-on software training. It offers over 8000 video tutorials on a range of software programs. Simon Sez IT ensures stress-free eLearning and enhanced employee productivity--whether you implement new software or a technological upgrade in your work environment. With over 600,000 students from 180 countries, Simon Sez IT is the preferred online learning choice for individuals and businesses worldwide.
    Note: Published in October 2022. - Online resource; title from title details screen (O'Reilly, viewed November 8, 2022)
    URL: lizenzpflichtig
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  • 46
    Online Resource
    Online Resource
    Python in practice : 15 projects to master Python (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781804618486 , 1804618489
    Language: English
    Pages: 1 online resource (1 video file (20 hr., 45 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: In this course, the initial few sections help you take a tour of programming in Python, covering all the basic to advanced concepts that are further used to build projects from scratch. You will create 15+ applications with Python. First, you will be creating a Dice Roller (a Python GUI application with Tkinter to generate random dice outputs) and Total Seconds and Days Counter. After that, you will create a Length Converter Python GUI application. Next, you will work on the image-to-icon converter to convert .png, .jpg, and .jpeg images into icons. You will work on a random element selector, perform data analysis and data visualization with the help of NumPy, Pandas, and matplotlib. You will also create a trees survey report, user credentials data, and sales data report. You will create eBook Store with Django 3 and an eCommerce website with HTML, CSS, and Bootstrap. You will also create a weight predictor, rainy or clear weather, and flavor predictor. Finally, you will make a rating bot, which will create a natural language processing model to rate comments and reviews automatically, and Face Recognizer that performs human face recognition with computer vision and OpenCV. By the end of this course, you will have learned the programming fundamentals to an advanced level with Python 3 and become an advanced-level programmer. What You Will Learn Learn about built-in functions in Python and how to create one Create a Python GUI application with Tkinter to generate random dice outputs Analyze the sales report in a week with Python data analysis Generate a survey report with data science Create an NLP model to rate comments and reviews automatically Perform human face recognition with computer vision and OpenCV Audience This course is ideal for individuals curious about Python programming, beginners at programming, and Python developers curious about data science, data analysis, and data visualization. This will also help full-stack web developers, artificial intelligence researchers, machine learning researchers, and GUI application developers. You just need curiosity and enthusiasm to get going with this course; the rest of everything will be taught from scratch. About The Author Rahul Mula: Rahul Mula is a developer specializing in Python, Flutter, and web development. He was really intrigued the first time he learned about programming and realized what could be done with it. He loves to explore different technologies and create applications to build something new. He has developed Keyviz--the free and open-source tool to visualize keystrokes in real-time. He has written books and created courses on Python programming teaching thousands of students.
    Note: Online resource; title from title details screen (O'Reilly, viewed November 21, 2022)
    URL: lizenzpflichtig
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  • 47
    Online Resource
    Online Resource
    The ultimate guide to Python programming with Python 3.10 (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781804612767 , 1804612766
    Language: English
    Pages: 1 online resource (1 video file (14 hr., 30 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Python is a fantastic object-oriented programming language that lets you use functional and OOP paradigms. Python offers several benefits compared to other programming languages such as Java, C++, or R. It is a dynamic language, with high-level datatypes. Python is easy to learn for beginners, being more readable and intuitive. With this course, you will learn about computer architecture, programming concepts, and what terminals are. You will install and set up Python on your computer and learn about hands-on programming with Python basics, client-info application, and console IO. You will code with data types, loops, functions, classes and objects, and modules and packages. Finally, you will learn about strings, stack and data structures, pip - python package manager, virtual environments, iterables, File IO, threading and multiprocessing, and debugging. Upon completion, you can easily handle any programming project and use core Python features. Create different array data structures, lists, tuples, sets, typed arrays, stacks, queues, and priority queues. Use structural pattern matching with match-case statements in Python 3.10 and third-party packages and create virtual environments for projects. What You Will Learn Implement basic data structures and basic programming with Python Create array structures such as a list, tuple, set, stack, and queue Learn object-oriented programming with Python classes and objects Use structural pattern matching with case statement in Python 3.10 Use Python REPL to write code from the terminal and test ideas Create virtual environments for projects with third-party packages Audience This course is beneficial for those with some skills in Python or if you are looking to refresh your skills and advance to the next level. Even if you can use a computer, that's completely fine as the course will train you to become a professional in coding. Complete newbies who want to learn to program or even beginner Python developers seeking expertise in Python programming can ace Python with this course. The course does not have any special requirements except turning the computer on and watching and learning from the course phase-by-phase. About The Author Rahul Mula: Rahul Mula is a developer specializing in Python, Flutter, and web development. He was really intrigued the first time he learned about programming and realized what could be done with it. He loves to explore different technologies and create applications to build something new. He has developed Keyviz--the free and open-source tool to visualize keystrokes in real-time. He has written books and created courses on Python programming teaching thousands of students.
    Note: Online resource; title from title details screen (O'Reilly, viewed November 21, 2022)
    URL: lizenzpflichtig
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  • 48
    Online Resource
    Online Resource
    Python : object-oriented programming (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781837638765 , 1837638764
    Language: English
    Pages: 1 online resource (1 video file (3 hr., 31 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Object-oriented programming (Computer science) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Python is a fantastic OOP language that lets you use functional and OOP paradigms. Python offers several benefits compared to other programming languages like Java, C++ or R. It is a dynamic language, with high-level data types. Python is easier to learn for beginners as its codes are more readable and intuitive. This course is designed to take you through the fundamentals of OOPs and understanding how it works. During this course, you will learn about important concepts such as classes, objects, abstraction, method overloading, and inheritance in sufficient detail. The course will also take you through the concepts of objects and attributes, mathematical operators, callable functions, encapsulation, inheritance and method resolution comprehensively. The course explains the OOP paradigm and lets you create class hierarchies using the OOP design process. By the end of the course, you will be able to design and implement Python programs for complex issues and make good use of the OOP features like classes and inheritance and apply your knowledge completing assignments that simulate real-world scenarios. What You Will Learn Create class hierarchies using the object-oriented design process Understand the difference between class and instance variables Make an object indexable, callable, and comparable Design and implement Python programs for complex problems Put to code the language features such as classes and inheritance Tackle complex code with OOP paradigm, design, and implementation Audience This course provides new developers who know Python basics to expand their knowledge and developers and learners who wish to learn OOP in Python. Developers involved with game development, GUI programming, AI, machine learning, and other computed automation can benefit from this course. The concepts and techniques can be applied to other programming languages, so intermediate-level developers wishing to advance their programming skillsets can also learn from this course for career advancement. To get the most from this course, you need to be an intermediate-level programmer in Python. About the Author Simon Sez IT: Simon Sez IT has offered technical courses since 2008 for individuals, small businesses, and Fortune 500 companies with thousands of employees who can benefit from the easy-to-learn and hands-on software training. It offers over 8000 video tutorials on a range of software programs. Simon Sez IT ensures stress-free eLearning and enhanced employee productivity--whether you implement new software or a technological upgrade in your work environment. With over 600,000 students from 180 countries, Simon Sez IT is the preferred online learning choice for individuals and businesses worldwide.
    Note: "Simon Sez IT.". - Published in October 2022. - Online resource; title from title details screen (O'Reilly, viewed November 8, 2022)
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