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  • Sciences, AI  (10)
  • [Erscheinungsort nicht ermittelbar] : Packt Publishing  (10)
  • 1
    Online-Ressource
    Online-Ressource
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    ISBN: 9781801077453
    Sprache: Englisch
    Seiten: 1 online resource (1 video file, approximately 9 hr., 28 min.)
    Ausgabe: 1st edition
    Schlagwort(e): Electronic videos ; local
    Kurzfassung: Dive into the world of machine learning and create projects with real-world applications About This Video Build a face recognition application from scratch Prepare and train your data for your projects Learn real-world applications of your algorithms In Detail Machine learning is a field of computer science through which you can create complex models that perform multiple functions using mathematical input. Python is a popular choice to create machine learning models due to a plethora of libraries easily accessible. This course takes you through this impressive combination of Python and machine learning, teaching you the basics of machine learning to create your own projects. You’ll begin learning about different types of machine learning models and how to choose the relevant ones for your project. You’ll learn to optimize this model and apply performance metrics to track its performance. You’ll also learn topics like regression, classification, and clustering to improve the performance of your model. You’ll learn the basics of neural networks and use scikit-learn to perform calculations in your project. By the end of this course, you’ll have created a face recognition application using everything you’ve learned in this course.
    Anmerkung: Online resource; Title from title screen (viewed April 23, 2021) , Mode of access: World Wide Web.
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 2
    Online-Ressource
    Online-Ressource
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    ISBN: 9781801071833
    Sprache: Englisch
    Seiten: 1 online resource (1 video file, approximately 11 hr., 10 min.)
    Ausgabe: 1st edition
    Schlagwort(e): Electronic videos ; local
    Kurzfassung: Learn machine learning and support vector machine from scratch About This Video Learn how to use Pandas for data analysis Learn how to use sci-kit-learn for SVM using the Titanic dataset Learn about training data, testing data, and outliers In Detail This course is truly a step by step. In every new video, we build on what has already been learned and move one extra step forward; then we assign you a small task that is solved in the beginning of the next video. 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 a human; based on that learning, your machine starts making predictions as well! We’ll be using Python as the programming language in this course, which is the hottest language nowadays when we talk about machine learning. Python will be taught from a very basic level up to an advanced level so that any machine learning concept can be implemented. We’ll also learn various steps of data preprocessing, which allows us to make data ready for machine learning algorithms. We’ll learn all the general concepts of machine learning, which will be followed by the implementation of one of the most important ML algorithms— “Support Vector Machine”. Each and every concept of SVM will be taught theoretically and implemented using Python.
    Anmerkung: Online resource; Title from title screen (viewed April 28, 2021) , Mode of access: World Wide Web.
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  • 3
    Online-Ressource
    Online-Ressource
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    ISBN: 9781803239248
    Sprache: Englisch
    Seiten: 1 online resource (1 video file, approximately 11 hr., 46 min.)
    Ausgabe: 1st edition
    Schlagwort(e): Electronic videos
    Kurzfassung: Learn to develop applications using MongoDB from scratch with this beginner-friendly course About This Video Relate the concepts and practical applications of MongoDB with real-world problems Implement any project from scratch that requires MongoDB knowledge Know the theoretical and practical aspects of MongoDB In Detail MongoDB, a fast and scalable NoSQL database, is extremely popular right now. This object-oriented database is simple and dynamic. In this course, you start by becoming proficient in the elementary concepts of MongoDB, including installing and setting up MongoDB Atlas, and understanding the database structure, collection structure, document structure, and basic Mongo commands. Next, you'll explore the Basic, Create, Read, Update, and Delete operations in MongoDB. You'll then explore in detail the MongoDB query operators and project operators. Following this, you'll learn about MongoDB update operators. In the concluding modules, you'll explore MongoDB with Node and Python. In the final module, you'll sharpen your practical knowledge of the theoretical concepts you learned in this course by working on two mini-projects. In the first project, you'll work on MongoDB with Django, in which you'll develop a CRUD-based application using Django and MongoDB. In the second project, you'll implement an ETL pipeline using PySpark to dump the data in MongoDB. By the end of this course, you will be able to implement any project from scratch that requires MongoDB knowledge. Who this book is for This course is designed for absolute beginners. As a newbie in this field, you will spend sufficient time - in gaining a thorough understanding of the fundamental concepts. You also need a good understanding of SQL. If you want to become a data scientist, database administrator, database engineer, or data engineer, then this course is for you.
    Anmerkung: Online resource; Title from title screen (viewed October 25, 2021) , Mode of access: World Wide Web.
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  • 4
    Online-Ressource
    Online-Ressource
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    ISBN: 9781801815949
    Sprache: Englisch
    Seiten: 1 online resource (1 video file, approximately 26 hr., 51 min.)
    Ausgabe: 1st edition
    Schlagwort(e): Electronic videos
    Kurzfassung: Explore the world of Computer Vision and learn to master it using Python, OpenCV, TensorFlow, and others About This Video Relate the concepts and theories in Computer Vision with real-world problems Know the theoretical and practical aspects of Computer Vision concepts Build applications for change detection in the live feed of cameras using Computer Vision techniques with Python In Detail The high-quality content of the Mastering Computer Vision from the Absolute Beginning Using Python course presents you with a great opportunity to learn and become an expert. You will learn the core concepts of the CV field. This course will also help you understand the digital imaging process and identify the key application areas of CV. The course is easy to understand, descriptive, comprehensive, practical with live coding, and rich with state-of-the-art and updated knowledge of this field. Although this course is a compilation of all the basic concepts of CV, you are encouraged to step up and experience more than what you learn. Your understanding of every concept is tested at the end of each section. The homework assignments/tasks/activities/quizzes along with solutions will assess your learning. Several of these activities are focused on coding so that you are ready to run with implementations. The two hands-on projects in the last section—Change Detection in CCTV Cameras (Real-Time) and Smart DVRs (Real-Time)—make up the most important learning element of this course. They will help you sharpen your practical skills. Successful completion of these two projects will help you enrich your portfolio and kick-start your career in the CV field. By the end of the course, you will have a strong understanding of Computer Vision concepts and will be ready to apply them in your future projects. Who this book is for This course is useful for data scientists, machine learning experts, and learners who are absolute beginners and know nothing about Computer Vision, and for people who want to learn Computer Vision with real data along with its implementation in realistic projects.
    Anmerkung: Online resource; Title from title screen (viewed September 23, 2021) , Mode of access: World Wide Web.
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  • 5
    Online-Ressource
    Online-Ressource
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    ISBN: 9781803230146
    Sprache: Englisch
    Seiten: 1 online resource (1 video file, approximately 93 hr., 31 min.)
    Ausgabe: 1st edition
    Schlagwort(e): Electronic videos
    Kurzfassung: The complete roadmap for beginners to data science and machine learning. About This Video Advanced and recently discovered models and breakthroughs by the champions in the AI field Key data science and machine learning concepts with examples in Python Detailed explanation and live coding with Python In Detail This course is crafted to teach you the most in-demand skills in the real world. This course aims to help you understand all the data science and machine learning concepts and methodologies with regard to Python. When you take a quick look at the different sections of this course, you may think of these sections as being independent. However, these sections are interlinked and almost sequential. Each section is an independent concept and is like a course on its own. We have deliberately arranged these sections in a sequence as each subsequent section builds upon the sections you have completed. This framework enables you to explore more independent concepts easily. At the end of every subsection, you are assigned homework to further strengthen your learning. All these assessments are based on the previous concepts and methods you have learned. Several of these assessment tasks will be coding-based, as the main aim is to get you up and proceeding to implementations. By the end of this course, you will be able to easily tackle real-world problems and ensure steady career growth and will be equipped with the knowledge of all the essential concepts you need to excel as a data science professional. Who this book is for This course is designed for people who want to become perfect in their data speak; people who want to learn data science and machine learning with real datasets in data science; people from a non-engineering background who want to enter the data science field; people who want to enter the machine learning field; people who want to learn data science and machine learning along with its implementation in realistic projects. For this course, no prior knowledge is needed. You will start with the basic concepts and gradually build your knowledge of the subject.
    Anmerkung: Online resource; Title from title screen (viewed November 30, 2021) , Mode of access: World Wide Web.
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  • 6
    Online-Ressource
    Online-Ressource
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    ISBN: 9781801078795
    Sprache: Englisch
    Seiten: 1 online resource (1 video file, approximately 12 hr., 17 min.)
    Ausgabe: 1st edition
    Schlagwort(e): Electronic videos ; local
    Kurzfassung: Learn data visualization from scratch About This Video Learn data manipulation and visualization from scratch Master various Python libraries such as NumPy, Pandas, Matplotlib, and so on Create interactive, insightful visualizations In Detail Data visualization has gained a lot of traction resulting from an increased focus on data analytics. To be a successful data scientist, data manipulation and wrangling is not enough. Visualizing data to garner insights is an equally important tool in the data science toolkit. Given the myriad types of data that exist, visualization has become an increasingly important topic. This course will equip you with all the skills you need to successfully create insightful visualizations. The course first starts with the fundamentals of Python. Then, the course teaches you how to use libraries such as NumPy, Pandas, Matplotlib, Seaborn, Bokeh, and so on. Additionally, you will learn data manipulation, which is the step prior to visualization. You will also learn how to plot geographical data using Folium. Each module in the course has practical hands-on mini projects. Hence, you not only learn the theoretical fundamentals of visualizations but also gain essential practical skills. With over 12 hours of content, this is one of the most comprehensive courses you will be doing on data visualization in Python.
    Anmerkung: Online resource; Title from title screen (viewed March 26, 2021) , Mode of access: World Wide Web.
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  • 7
    Online-Ressource
    Online-Ressource
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    ISBN: 9781801075091
    Sprache: Englisch
    Seiten: 1 online resource (1 video file, approximately 12 hr., 32 min.)
    Ausgabe: 1st edition
    Schlagwort(e): Electronic videos ; local ; Electronic videos
    Kurzfassung: A comprehensive course that teaches you the concepts and methodologies of statistics and probability with data science. About This Video Easy explanations, yet complete and comprehensive course Fundamental, pythonic, and a complete course to master the important concepts used in data science Practical with live coding of the implementation of the concepts learned theoretically In Detail In today's ultra-competitive business universe, probability and statistics are the most important fields of study. That is because statistical research presents businesses with the data they need to make informed decisions in every business area, whether it is market research, product development, product launch timing, customer data analysis, sales forecast, or employee performance. But why do you need to master probability and statistics in Python? The answer is that an expert grip on the concepts of statistics and probability with data science will enable you to take your career to the next level. This course is designed carefully to reflect the most in-demand skills that will help you in understanding the concepts and methodology with regard to Python. The course is as follows: Easy to understand Expressive Comprehensive Practical with live coding About establishing links between probability and machine learning By the end of this course, you will be able to relate the concepts and theories in machine learning with probabilistic reasoning and understand the methodology of statistics and probability with data science, using real datasets.
    Anmerkung: Online resource; Title from title screen (viewed June 28, 2021) , Mode of access: World Wide Web.
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  • 8
    Online-Ressource
    Online-Ressource
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    ISBN: 9781803248653
    Sprache: Englisch
    Seiten: 1 online resource (1 video file, approximately 12 hr., 48 min.)
    Ausgabe: 1st edition
    Schlagwort(e): Electronic videos ; local ; Electronic videos
    Kurzfassung: Learn Scala; learn Spark, Hadoop, ETL pipeline from AWS S3 to AWS RDS using Spark from scratch About This Video Relate the practical concepts of Scala and Spark with real-world problems Implement any project from scratch that requires Scala and Spark knowledge Know the theoretical and practical aspects of Scala and Spark In Detail The course Scala from Beginner to Pro is refreshingly different. The well-thought-out quizzes and mini projects that cover all the important aspects will make your Scala learning journey that much easier. This course includes an overview of Hadoop and Spark with a hands-on project with Scala Spark. Right through the course, every theoretical explanation is followed by practical implementation. This course is designed to reflect the most in-demand Scala skills that you will start using right away at the workplace. The course is simple to follow and understand. Expressive, exhaustive, and practical with live coding sessions and replete with quizzes. Rich with state-of-the-art and up-to-date knowledge of this field. The 6 mini-projects and one Scala Spark project included in this course are a vital component of this course. These projects present you with a hands-on opportunity to experiment for yourself with trial and error. You get a chance to learn from the mistakes you make. Importantly, it’s easy to understand the potential gaps that might exist between theory and practice. Who this book is for This course is for absolute beginners who want to learn Spark and Scala along with its implementation in realistic projects; people who want to develop smart solutions; data scientists; and machine learning experts.
    Anmerkung: Online resource; Title from title screen (viewed August 27, 2021) , Mode of access: World Wide Web.
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 9
    Online-Ressource
    Online-Ressource
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    ISBN: 9781803236698
    Sprache: Englisch
    Seiten: 1 online resource (1 video file, approximately 16 hr., 11 min.)
    Ausgabe: 1st edition
    Schlagwort(e): Electronic videos
    Kurzfassung: Master Spark, PySpark AWS, Spark applications, Spark Ecosystem, Hadoop, and mastering PySpark About This Video Relate the concepts and practical aspects of Spark and AWS with real-world problems Implement any project that requires PySpark knowledge from scratch Know the theory and practical aspects of PySpark and AWS In Detail The hottest buzzwords in the Big Data analytics industry are Python and Apache Spark. PySpark supports the collaboration of Python and Apache Spark. In this course, you'll start right from the basics and proceed to the advanced levels of data analysis. From cleaning data to building features and implementing machine learning (ML) models, you'll learn how to execute end-to-end workflows using PySpark. Right through the course, you'll be using PySpark to perform data analysis. You'll explore Spark RDDs, Dataframes, and a bit of Spark SQL queries. Also, you'll explore the transformations and actions that can be performed on the data using Spark RDDs and Dataframes. You'll also explore the ecosystem of Spark and Hadoop and their underlying architecture. You'll use the Databricks environment to run the Spark scripts and explore it as well. Finally, you'll have a taste of Spark with AWS cloud. You'll see how we can leverage AWS storages, databases, computations, and how Spark can communicate with different AWS services and get its required data. By the end of this course, you'll be able to understand and implement the concepts of PySpark and AWS to solve real-world problems. Who this book is for This course requires python programming experience as a prerequisite.
    Anmerkung: Online resource; Title from title screen (viewed September 23, 2021) , Mode of access: World Wide Web.
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  • 10
    Online-Ressource
    Online-Ressource
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    ISBN: 9781801818483
    Sprache: Englisch
    Seiten: 1 online resource (1 video file, approximately 13 hr., 49 min.)
    Ausgabe: 1st edition
    Schlagwort(e): Electronic videos
    Kurzfassung: Learn web scraping and data mining from scratch using Python About This Video Relate the concepts and practical aspects of data scraping with real-world problems Know the theory and practical aspects of data scraping concepts Implement any project from scratch that requires data scraping knowledge In Detail Data scraping is the technique of extracting data from the Internet. The course Data Scraping and Data Mining from Beginner to Professional is crafted to cover topics that result in the development of the most in-demand skills in the workplace. These topics will help you understand the concepts and methodologies with regard to Python. The course is easy to understand, imaginative and descriptive, comprehensive, practical with live coding, full of quizzes with solutions, rich with state-of-the-art and updated knowledge of this field. This course is designed for beginners. We'll spend sufficient time on the fundamentals. Then, we will gradually go far deep with a lot of practical implementations where every step will be explained in detail. As this course is essentially a compilation of all the basics, you will move ahead at a steady rate. You will experience more than what you have learned. Most of these activities are designed to get you up and running with implementations. The four hands-on projects included are the most important part of this course. These projects allow you to experiment for yourself with trial and error. You will learn from your mistakes. Importantly, you will understand the potential gaps that may exist between theory and practice. Who this book is for This course is for people who are beginners and absolutely new to data scraping and for individuals who want to make smart solutions and learn data scraping with real data using Python. It is also useful for data scientists, machine learning experts, drop shippers who are interested in learning data scraping along with its implementation in realistic projects.
    Anmerkung: Online resource; Title from title screen (viewed September 23, 2021) , Mode of access: World Wide Web.
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