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  • MPI Ethno. Forsch.  (9)
  • HU Berlin
  • München BSB
  • München UB
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  • Englisch  (9)
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  • 1
    Online-Ressource
    Online-Ressource
    [Place of publication not identified] : Addison-Wesley Professional
    ISBN: 9780138107710 , 0138107718
    Sprache: Englisch
    Seiten: 1 online resource (1 video file (12 hr., 25 min.)) , sound, color.
    Ausgabe: [First edition].
    DDC: 004.67/82
    Schlagwort(e): Amazon Web Services (Firm) ; Cloud computing ; Web sites Design ; Web site development ; Instructional films ; Nonfiction films ; Internet videos
    Kurzfassung: Learn to create applications using AWS services today. Hands-on Development in AWS teaches core concepts for using AWS services to create real-world applications. Explore the fundamentals before diving into database and storage, messaging, and execution services so you can create the applications you need to develop. Expert trainer and author Nick Garner will give you hands-on practical experience to create an application and run the application in the cloud. This is a lab-based approach to learning that gives you the opportunity to learn through exercises.
    Anmerkung: Online resource; title from title details screen (O'Reilly, viewed January 23, 2023)
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  • 2
    Online-Ressource
    Online-Ressource
    [Place of publication not identified] : Addison-Wesley Professional
    ISBN: 9780138227869 , 0138227861
    Sprache: Englisch
    Seiten: 1 online resource (1 video file (16 hr., 17 min.)) , sound, color.
    Ausgabe: [First edition].
    Serie: Live lessons
    Serie: Video collection
    DDC: 658.15
    Schlagwort(e): Business enterprises Finance ; Business enterprises Case studies Finance ; Data mining ; Instructional films ; Nonfiction films ; Internet videos
    Kurzfassung: 16+ Hours of Video Instruction Predictive and Prescriptive Analytics (Video Collection) brings a holistic, approachable, and best practice-driven learning experience to predictive and prescriptive analytics. It gives direct Instruction in the Foundations, Methods, Applications, and Best Practices to the highest pillars of business analytics. This master class includes the following courses: Predictive Analytics, 2nd Edition, LiveLessons Prescriptive Analytics for Optimal Decision-Making LiveLessons Overview Updated and revamped, Predictive Analytics LiveLessons, 2nd Edition provides comprehensive (yet easy-to-digest) coverage of business analytics concepts, applications, methods, and tools, with a special emphasis on predictive modeling and analysis. Over the course of the eight lessons, you will learn fundamental concepts, methods, and algorithms of business analytics and data mining, as well as their application areas and best practices. You also learn how to use a variety of software tools (both commercial as well as free/open source) and how to use those tools to discover knowledge from a wide variety of data sources. At the end of the course, you will not only know what predictive analytics is and what it can do for an organization but also develop basic skills to practice predictive analytics using numerous tools and platforms, most of which are free and open source. The course is designed to provide thorough coverage of the underlying concepts and definitions of predictive analytics in order to demystify the concepts and terminology of these popular evidence-based managerial decisioning trends and then help build hands-on skills with the most popular analytics tools and platforms using intuitive examples and data sets. Prescriptive Analytics for Optimal Decision-Making LiveLessons is designed and developed to provide comprehensive coverage of the underlying concepts and definitions of business analytics, and specifically prescriptive analytics, in order to clarify the confusion about the already crowded terminology and buzzwords for these popular evidence-based managerial decisioning trends. Prescriptive analytics are where the optimal decisions are made, often based on the information provided by descriptive and predictive analytics layers. The lesson structure in this course provides a natural progression of the foundational concepts, methods, and methodologies of prescriptive analytics as well as their application areas, the best practices, a variety of software tools, and how to use those tools to identify the best decision for a given, often overly complex, real-world problem. Based on this foundational understanding, the course builds hands-on skills with a variety of popular prescriptive analytics tools and platforms (including Microsoft Excel) using intuitive examples and simplified data sets. The key idea is to build both awareness and in-depth understanding of prescriptive analytics best practices through intuitive, visual, and hands-on applications and case studies. About the Instructor Dr. Dursun Delen is an internationally renowned expert in business analytics, data science, machine learning, and data mining. He is often invited to national and international conferences to deliver keynote presentations on topics related to data/text mining, business intelligence, decision support systems, business analytics, data science, and knowledge management. Prior to his appointment as a professor at Oklahoma State University in 2001, Dr. Delen worked in industry for more than 15 years, developing and delivering business analytics solutions to companies. His most recent industrial work was at a privately owned applied research and consulting company, Knowledge Based Systems, Inc. (kbsi.com), in College Station, Texas, as a research scientist. During his five years at KBSI, Dr. Delen led a number of projects related to decision support systems, enterprise engineering, information systems development, and advanced business analytics that were funded by private industry and federal agencies, including several branches of the Department of Defense, NASA, National Science Foundation, National Institute for Standards and Technology, and the Department of Energy. Today, in addition to his academic endeavors, Dr. Delen provides professional education, mentoring, and consulting services to businesses in assessing their analytics, data science and information system needs, and helping them in developing state-of-the-art computerized decision support systems. He has published over 180 peer-reviewed research articles that appeared in major journals. He has also authored eleven books and textbooks in the broad area of business analytics, data science, and business intelligence. Dr. Delen regularly chairs tracks and minitracks at various business analytics and information systems conferences. Currently, he is the editor-in-chief of the Journal of Business Analytics and AI in Business (in Frontiers in Artificial Intelligence), senior editor for the Journal of Decision Support Systems, decision sciences, and Journal of Business Research, associate editor for decision analytics, International Journal of Information and Knowledge Management, and International Journal of RF Technologies, and is on the editorial boards of several other academic journals. He has been the recipient of several research and teaching awards including the prestigious Fulbright scholar, regents' distinguished teacher and researcher, president's outstanding researcher, and big data mentor awards. About Pearson Video Training Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Prentice Hall, Sams, and Que Topics include: IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more. Learn more about Pearson Video training at http://www.informit.com/video.
    Anmerkung: Online resource; title from title details screen (O'Reilly, viewed April 11, 2023)
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  • 3
    Online-Ressource
    Online-Ressource
    [Place of publication not identified] : Addison-Wesley Professional
    ISBN: 9780137949083 , 0137949081
    Sprache: Englisch
    Seiten: 1 online resource (1 video file (7 hr., 16 min.)) , sound, color.
    Ausgabe: [First edition].
    Serie: Live lessons
    DDC: 005.1
    Schlagwort(e): Computer software Development ; Computer software ; Development ; Instructional films ; Internet videos ; Nonfiction films ; Instructional films ; Nonfiction films ; Internet videos
    Kurzfassung: Approximately 8 Hours of Video Instruction If your development team is still dealing with manual and repetitive build- or deployment-related tasks, this course is for you. Overview Software is at the center of our world and touches nearly everything we do. The world depends on great software and access to features at the speed of innovation. Agile processes and mindsets help teams build features iteratively and get feedback quickly to apply learning and correct courses; however, without concepts like DevOps to remind us of what's possible, feedback and innovation hit a dead end or an unnatural pause. To consider yourself or your team truly agile, you must embrace the concept of continuous delivery in its fullness. Continuous delivery is not a goal but a direction. By walking in the direction of continuous delivery, you get closer and closer on a daily basis to reaching a cadence where features and feedback truly move to users at the speed of innovation. Continuous Delivery is at the core of DevOps. About the Instructor Byron Sommardahl is a 30+ year veteran in software development, and his passion for great code and innovative products has never diminished. He went from floundering junior to sought-after senior and on to architect and CTO. Byron helped found and lead as many as 10 simultaneous projects. He has gathered a great deal of valuable knowledge in product ownership and agile engineering. His background in quality software development, project management, and expert product ownership has given him the knowledge to lead his teams and his clients to consistent success. That's why he started the Dev Amplifier Coaching Program, a weekly coaching community and accountability program designed to help you find and close your gaps in knowledge. Learn How To Influence development teams and stakeholders toward continuous delivery and improvement Write more maintainable scripts that enable CI/CD Instruct CI/CD systems using YAML notation Integrate your code automatically and continuously Automate deployment and verification of working software Inform team leadership with meaningful metrics Who Should Take This Course Software developers IT professionals Site reliability engineers (SRE) Course Requirements Scripting or programming skills Experience with Git Experience in deploying web-based projects to hosting providers An AWS account (free tier is okay) A GitHub account Some experience with agile software development and project management is nice Lesson Descriptions Lesson 1, "Delivering Value Consistently": This lesson defines CI/CD and Continuous Delivery, discuses Continuous Delivery as a direction and culture influencer instead of a just set of tools, and explains how to use metrics as a change agent to influence organizational culture. Lesson 2, "Foundations of Sound CI/CD": This lesson teaches scripting options and how to manage them. It also covers YAML syntax and its application in print scenarios in the CI/CD world. Lesson 3, "Continuous Integration": This lesson teaches teams using CI/CD how to shorten feedback loops by failing fast. It also shows how to test various components of Continuous Integration in preparation for completing the artifact build. Lesson 4, "Continuous Deployment": This lesson builds on Continuous Integration teachings in previous lessons by adding technologies and components of Continuous Deployment to move the artifact into the cloud or into a server for public consumption. This lesson also discusses advanced triggering methods to prompt old build jobs to start at different times and for different reasons. It also covers different reusable actions. Lesson 5, "Deployment Strategies": This lesson unpacks different ways to think about deployments. It covers popular patterns and strategies for deploying distributive systems, as well as how to plan a refactor or new implementation. Lesson 6, "Infrastructure Management": This lesson discusses advanced CI/CD practices, such as directing the infrastructure management tool that is best for you and your team, spinning up and tearing down infrastructure in response to rollbacks, and implementing all of this within your CI/CD pipeline. Lesson 7, "Configuration Management": This lesson shows how to integrate configuration management tools into your CI/CD pipeline to enable automation. It discusses how to define your configuration changes ahead of time so that they can be stored in your source control alongside your code, and how to use scripting to deploy changes to remote machines. Lesson 8, "Continuous Delivery": This lesson discusses where DevOps fits in the greater organizational culture and Continuous Delivery at large, as well as cultural changes necessary to keep Continuous Delivery alive and how to measure the adoption of that change. About Pearson Video Training Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Prentice Hall, Sams, and Que. Topics include IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more. Learn more about Pearson Video training at http://www.informit.com/video.
    Anmerkung: Online resource; title from title details screen (O'Reilly, viewed March 21, 2023)
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  • 4
    Online-Ressource
    Online-Ressource
    [Place of publication not identified] : Addison-Wesley Professional
    ISBN: 9780138039103 , 0138039100
    Sprache: Englisch
    Seiten: 1 online resource (1 video file (2 hr., 53 min.)) , sound, color.
    Ausgabe: [First edition].
    Serie: Live lessons
    DDC: 005.1
    Schlagwort(e): Agile software development ; Project management ; Teams in the workplace ; Instructional films ; Nonfiction films ; Internet videos
    Kurzfassung: 4 Hours of Video Instruction Good metrics can help a team continuously improve and deliver consistently, while poor metrics can create a culture of fear; this video shows how to measure Agile teams effectively and help create an environment that maximizes value and learning. Overview Finding the right balance of metrics for your Agile teams can significantly help your continuous improvement efforts, forecasting, and risk management on software development projects. Instilling curiosity about performance data--instead of dreading arbitrary performance goals--is the best way to promote a culture of continuous improvement. This video will guide you through how best to incorporate metrics into your teams and organizations to diagnose issues, unearth trends, predict issues, and apply historical results to prescribe preventative actions. You will also learn multiple techniques and approaches for creating data visualizations that make your metric reporting clear and impactful. About the Instructor Tommy Norman (CSM, A-CSM, CSPO, CSP, CTC, CEC, CAL, PSM, SAFe Agilist, Microsoft MVP) is the Chief Agility Officer at Acklen Avenue, a custom software development shop in Nashville, TN. With an IT career spanning almost 30 years, he has been helping organizations of all sizes and shapes build great software with a practical approach in a multitude of roles. He has worked deeply with the Agile community as the coordinator of the Agile Nashville user group, founder of the Music City Agile conference, as well as a frequent local and international speaker. Learn How To Define a metric in a way to best observe and influence team behavior and avoid unwanted side effects. Effectively use standard deviation, thresholds, and boundaries to better understand your data trends and better identify potential risks. Understand the four types of data analytics (informative, diagnostic, predictive, and prescriptive) to get the most out of your metrics. Build and use a balanced metrics dashboard to create a culture of continuous improvement that maximizes value and learning. Create and define metrics that will influence team behaviors that maximize value and learning. Use metrics more effectively by incorporating the four types of data analytics: informative, diagnostic, predictive, and prescriptive. Create a balanced dashboard that can offer critical insights into how your teams are performing, feeling, and producing. Who Should Take This Course Agile Coach Scrum Master Delivery Manager/Product Owner Course Requirements Understanding of the fundamentals of Agile software development and frameworks such as Scrum and Kanban. Lesson descriptions Lesson 1: Why We Measure: This lesson discusses the underlying drivers for our data analytics and the importance of awareness and intent when measuring data. It's important to approach measuring data with the right intent. A common negative consequence of measuring data with the wrong intent is creating a culture of fear. Lesson 2: Defining a Metric: This lesson explores what is a good metric, how to use simple questions to best outline what to measure, and how to avoid some common pitfalls when working with data. Lesson 3: Descriptive Data Analytics: This lesson describes the first step to creating metrics, which is to collect and visualize historical data to see what's been happening with your team. Lesson 3 is a perfect example of the quote, "A picture maybe worth a thousand words but a good report is worth a thousand data points." Lesson 4: Diagnostic Data Analysis: This lesson explores the importance of understanding and uncovering why certain things happen with your team. Lesson 4 gives you behind-the-scenes kind of experience. Lesson 5: Predictive Data Analytics: This lesson shows about how to get a decent idea of what's likely to happen within your team since the future is unpredictable. The instructor gives tips and tricks of using empirical data and simple math to get ahead of potential issues that might arise going forward. Lesson 6: Prescriptive Data Analytics: This lesson shows how to analyze your data, identify trends therein, and make informed decisions for your team based on your analysis. Lesson 7: Creating a Balanced Dashboard: This lesson covers the importance of considering the full landscape of collected data, and how to find the best mix of connective metrics to inform your analysis. Lesson 8: Instilling a Culture of Continuous Improvement: This lesson shows how to use data safely while maintaining the freedom to experiment. You will learn to approach metrics in a way that inspires curiosity and not fear. Lesson 9: Agile Metrics in Action: This lesson consists of real-world examples of topics and tools covered in previous lessons, and is intended to help you understand how metrics work in agile teams and organizations. About Pearson Video Training Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Prentice Hall, Sams, and Que Topics include: IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more. Learn more about Pearson Video training at http://www.informit.com/video.
    Anmerkung: Online resource; title from title details screen (O'Reilly, viewed February 20, 2023)
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  • 5
    Online-Ressource
    Online-Ressource
    [Place of publication not identified] : Addison-Wesley Professional
    ISBN: 9780138189419 , 0138189412
    Sprache: Englisch
    Seiten: 1 online resource (1 video file (3 hr., 32 min.)) , sound, color.
    Ausgabe: [First edition].
    Serie: Live lessons
    DDC: 001.4/226
    Schlagwort(e): Tableau (Computer file) ; Information visualization ; Tableau (Computer file) ; Information visualization ; Instructional films ; Internet videos ; Nonfiction films ; Instructional films ; Nonfiction films ; Internet videos
    Kurzfassung: Nearly 4 Hours of Video Instruction A Visual Introduction to Visual Analytics Overview: Visual Analytics Fundamentals LiveLessons is a practical, hands-on guide to learning the basics of visual analytics. After you finish the videos you will be able to start building compelling visual data narratives using Tableau 2022. About the Instructor: Lindy Ryan is passionate about telling stories with data. She specializes in translating raw data into insightful stories through carefully curated visuals and engaging narrative frameworks. Lindy teaches courses in visual analytics, data visualization, and product design in the Professional Science Master's program at Rutgers, the State University of New Jersey. She also supports Western State Connecticut's MFA writing program as guest faculty to mentor aspiring writers working in their second genre. Lindy previously taught in the Montclair State University (MSU) Business Analytics program, where she received the MSU Professing Excellence Award, which recognizes professors' teaching excellence, particularly those who inspire and motivate students. She has been a Tableau user since 2012. Lindy is the author of The Visual Imperative: Creating a Culture of Visual Discovery (Elsevier Morgan Kaufmann, 2016) and Visual Data Storytelling with Tableau (Pearson Addison-Wesley, 2018), as well as numerous papers, book chapters, and conference presentations worldwide. Skill Level: Beginner Intermediate Learn How To: Navigate the Tableau interface Understand the role of context in visual analytic storytelling Decide which type of basic chart to use with type of data Use maps to represent data Make good design decisions regarding color, lines, and shapes Prepare your data and storyboard your visualization Use advanced visualization formats Who Should Take This Course: Analysts who need to share the results of their data discovery or analysis Students communicating data for reports or presentations Teachers helping learners (of any age) to cultivate visual data literacy Executives and business managers reporting data-driven results or metrics Journalists giving data the starring role in their editorials Course Requirements: A willingness to learn how to tell stories through data Access to Tableau Desktop (Windows or Mac), version 2022 or higher Lesson Descriptions: Lesson 1: Welcome to Visual Analytics Lesson 1 introduces you to the practice of visual analytics with an overview of the state of the data visualization industry. As a foundation for more in-depth explorations throughout this book, we explore how data visualization and visual data storytelling have become in-demand analytic job skills today. The lesson also explores how the two practices are similar and different, and how both are propelled by new technologies and bigger, more diverse, and more dynamic data. Finally, the role of communication skills within visual analytics is discussed along with a brief look at how academia is supporting the demand for visual analysts today. Lesson 2: The Power of Visual Analytics Memory, retention, and emotion form the bases for experience, all of which work in tandem with our brain's visual processing horsepower. This lesson leverages real-life examples to showcase the power of visual analytics and visual data stories to communicate discoveries and insights hidden in data. We review the role of human cognition in visual analytics; how the brain reacts to inputs of data, stories, and data stories as unique entities; and how we can leverage this power to tell effective data narratives and influence action. Lesson 3: Getting Started with Tableau Application requires an environment for practice as a first step toward efficacy. This lesson shifts the focus from theory to implementation as we briefly explore the different products contained within the Tableau application suite, focusing on the Tableau Desktop 2022 user interface. The lesson covers how to get started with Tableau Desktop, reviews the tool's user interface and basic functionality, and discusses how to connect to data and ensure it is properly prepared for analysis. From here you will be able to move on to the visual analytics process to curate visuals and build data dashboards and stories while building skills and competencies in the market-leading data visualization tool most in demand by today's employers. Lesson 4: Keeping Visual Analytics in Context This lesson describes the importance of understanding data's context and its role in helping visual analysts ask the right questions to build a data narrative framework. You learn about exploratory and explanatory analysis and strategies for successful data storytelling, including narrative flow, considerations for spoken versus written narratives that support visuals, and structures that can support your stories for maximum impact. The lesson also explores helpful techniques in Tableau that guide you in crafting effective data narrative structure and keeping data firmly connected to its context. Lesson 5: Fundamental Data Visualizations This lesson introduces the fundamental charts and graphs used to visually communicate data that are offered on the Tableau Show Me Card. The lesson discusses appropriate use cases for each and get you some hands-on opportunities to create examples in Tableau. You learn techniques to help you assess when to use each visualization type according to the data, how to generate these according to best practices, and helpful considerations for when to avoid certain types of charts. The lesson also explores some of the special features available in Tableau to help you get the most from your visualizations. Lesson 6: Fundamental Maps As a continuation of the previous lesson, this lesson introduces two fundamental types of maps available on the Tableau Show Me Card. Again, we discuss appropriate use cases for each and get hands-on to create examples in Tableau, as well as how to generate these according to best practices, and helpful considerations specifically for mapping data. The lesson also explores some of the special features available in Tableau to help you get the most from your maps. Lesson 7: Design Tips for Curating Visual Analytics This lesson dives into human cognition and visual perception to frame how pre-attentive attributes such as size, color, shape, and position affect the usability and efficacy of visual analytics. We explore best practices for how the design elements can be employed to direct an audience's attention and create a visual hierarchy of components to communicate effectively. Lesson 8: Structuring Analytics for Storytelling This lesson moves beyond the basics of visual analytics to take our first steps in architecting outputs of analysis in visual data dashboards and stories. We'll begin by taking a closer look at how to prepare data in Tableau, utilizing some messy survey data--a common experience for data storytellers--before building data dashboards and stories that incorporate features like filters, annotations, and highlights to present compelling, meaningful, and actionable outcomes of visual analytics. Lesson 9: Beyond Fundamentals: Advanced Visualizations This penultimate lesson explores advanced strategies that go beyond fundamental data visualizations to explore a curated set of advanced data visualizations beyond the Tableau Show Me Card. It covers how to create advanced charts that require additional formatting and calculations, including timelines, Likert scale charts, lollipop charts, and more. Lesson 10: Closing Thoughts You have covered a lot of ground in this series. This final lesson recaps the lessons and emphasizes the main takeaways. It also serves as a resource kit by providing checklists of best practices and practical suggestions for continuing to master outputs of visual analytics. It also discusses additional resources available to support you on this journey. About Pearson Video Training: Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Sams, and Que. Topics include IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more. Learn more about Pearson Video training at http://www.informit.com/video.
    Anmerkung: Online resource; title from title details screen (O'Reilly, viewed March 21, 2023)
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  • 6
    Online-Ressource
    Online-Ressource
    [Place of publication not identified] : Addison-Wesley Professional
    ISBN: 9780138224912 , 0138224919
    Sprache: Englisch
    Seiten: 1 online resource (1 video file (2 hr., 53 min.)) , sound, color.
    Ausgabe: [First edition].
    DDC: 006.3
    Schlagwort(e): ChatGPT ; Artificial intelligence ; Natural language processing (Computer science) ; Instructional films ; Nonfiction films ; Internet videos
    Kurzfassung: 3 Hours of Video Discover the astounding state-of-the-art in Natural Language Processing (NLP) that is enabled by Large Language Models (LLMs) like ChatGPT and T5 Understand Attention and Transformers, as well as how these essential modern NLP concepts relate to Deep Learning and LLMs Survey the staggeringly broad range of LLMs' natural-language capabilities Learn how to use LLMs in practice, including how to train and deploy them into production NLP applications Large Language Models (LLMs) such as GPT series architectures have dramatically accelerated the natural language processing (NLP) capabilities of machines in recent years. These capabilities, facilitated by LLMs' hundreds of billions of model parameters, approach or exceed human-level performance on a staggeringly broad set of natural-language tasks -- often without any task-specific training being required. In this event, leading subject-matter experts introduce LLMs and their associated concepts (e.g., Transformers, Attention), survey LLMs' breadth of capabilities, and provide the best practices on how to leverage LLMs efficiently and confidently in order to supercharge your own natural-language applications. AI Catalyst The AI Catalyst Conference from Pearson brings together leading voices in AI to make complex topics understandable and actionable. Host Jon Krohn guides the conversation and explains how to bring state-of-the-art methods into practice. Gain new information or a different perspective to make an impact in your job and in the world. By the end of the course, you'll understand: Large Language Models (LLMs) Attention Transformers The breadth of state-of-the-art NLP applications And you'll be able to: Select an appropriate LLM architecture for a given NLP application Prompt pre-trained LLMs like ChatGPT and GPT-3 to effectively produce your desired output Train and deploy LLMs into production NLP applications Potentially accelerate your data science roadmap by months or years by leveraging a pre-trained LLM instead of needing to train individual task-specific models from scratch yourself This course is for you because... You'd like to appreciate the staggering breadth of NLP and Deep Learning capabilities You are a data scientist, software developer, ML engineer, or other technical professional who would like to be able incorporate new NLP approaches into real-world applications Prerequisites All you need is an interest in how AI can impact you and your organization. Recommended Follow-up Read: Quick Start Guide to LLMs by Sinan Ozdemir, https://learning.oreilly.com/library/view/quick-start-guide/9780138199425/ Attend: Deploying GPT and Large Language Models by Sinan Ozdemir: https://learning.oreilly.com/search/?q=Sinan%20Ozdemir&type=live-event-series&rows=10&publishers=Pearson Attend: Hands-on Natural Language Generation and GPT by Sinan Ozdemir: https://learning.oreilly.com/search/?q=Sinan%20Ozdemir&type=live-event-series&rows=10&publishers=Pearson Read: Chapter 15 of Learning Deep Learning by Dr. Magnus Ekman: https://learning.oreilly.com/library/view/learning-deep-learning/9780137470198/ Watch: NLP using Transformer Architectures by Aur©♭lien G©♭ron: https://learning.oreilly.com/videos/natural-language-processing/0636920373605/0636920373605-video329383/ For a more general introduction to deep learning, check out the Deep Learning: The Complete Guide playlist by Dr. Jon Krohn: https://learning.oreilly.com/playlists/a40ea8fe-994d-4370-8b29-0d6c0f519a89/ Course Schedule Jon Krohn: Welcome Sinan Ozdemir: Introduction to Large Language Models (30 minutes) We can't talk about state-of-the-art Natural Language Processing (NLP) without talking about Transformers and large language models (LLMs) like ChatGPT, BERT, GPT, and T5. Sinan explores a brief history of modern NLP up to the rise of attention-based models and Transformers including the proliferation of LLMs that continues to this day along with all of the good and sometimes the not-so-good outcomes. He overviews the major architectures that influence the tasks and models that dominate NLP while peeking under the hood to understand how LLMs learn to read, write, and do so much more. Sinan Ozdemir is an active lecturer focusing on large language models and a former lecturer of data science at the Johns Hopkins University. He is the author of multiple textbooks on data science and machine learning including The Principles of Data Science. Sinan is the Founder and CTO of LoopGenius where he uses State of the art AI to help people create and run their businesses. He holds a master's degree in Pure Mathematics from Johns Hopkins University and is based in San Francisco. Jon and Sinan Discussion + Q&A Melanie Subbiah: The Broad Range of LLM Capabilities Large language models have unlocked a huge number of exciting applications in the real world that were not possible before -- capabilities that are creative, useful, and profitable. Through interactive demos of GPT-3, Melanie explores a broad range of these use cases, giving participants more intuition for how large language models have been effective. Melanie Subbiah is a third-year PhD student in NLP at Columbia University where she researches narrative summarization and aspects of online text safety. Before starting graduate school, she was one of the lead authors on the GPT-3 paper, building out the evaluation suite for that work and helping early customers use the OpenAI API for their projects. Prior to that, she researched autonomous systems at Apple. Melanie obtained her Bachelor's in computer science from Williams College. Jon and Melanie Discussion + Q&A Shaan Khosla: Training and Deploying LLMs Shaan covers practical LLM tips over the full NLP lifecycle. These include topics such as efficient training practices, validation methods, and productionization considerations to ensure your design is optimized for implementation within your real-world natural-language application. Shaan Khosla is a data scientist at Nebula where he researches, designs, and develops NLP models. He's previously worked at Bank of America on an internal machine learning consulting team, where he used LLMs to build proof of concept systems for various lines of business. Shaan holds a BSBA in Computer Science and Finance from the University of Miami and is currently completing a master's degree in Data Science at NYU. He has published multiple peer-reviewed papers applying LLMs, topic modeling, and recommendation systems to the fields of biochemistry and healthcare. Jon and Shaan Discussion + Q&A Jon Krohn: Closing Remarks About the Host Host: Jon Krohn is Co-Founder and Chief Data Scientist at the machine learning company Nebula. He authored the book Deep Learning Illustrated, an instant #1 bestseller that was translated into seven languages. He is also the host of SuperDataScience, the data science industry's most listened-to podcast. Jon is renowned for his compelling lectures, which he offers at leading universities and conferences, as well as via his award-winning YouTube channel. He holds a PhD from Oxford and has been publishing on machine learning in prominent academic journals since 2010.
    Anmerkung: Online resource; title from title details screen (O'Reilly, viewed April 11, 2023)
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  • 7
    Online-Ressource
    Online-Ressource
    [Place of publication not identified] : Addison-Wesley Professional
    ISBN: 9780138050764 , 0138050767
    Sprache: Englisch
    Seiten: 1 online resource (1 video file (7 hr., 31 min.)) , sound, color.
    Ausgabe: [First edition].
    Serie: Live lessons
    DDC: 005.13/3
    Schlagwort(e): Python (Computer program language) ; Computer programming ; Computer programming ; Python (Computer program language) ; Instructional films ; Internet videos ; Nonfiction films ; Instructional films ; Nonfiction films ; Internet videos
    Kurzfassung: 7.5 Hours of Video Instruction In Learn Enough Python to Be Dangerous: A Tutorial Introduction to Programming with Python, renowned instructor Michael Hartl teaches you to write practical and modern programs using the elegant and powerful Python programming language. Overview Programmers love Python for its clean syntax, flexible data types, a wealth of useful libraries, and a powerful and elegant design that supports multiple styles of programming. That's why it is popular for varied uses such as scripting, web development, and data science. You'll love Python too, but you don't need to learn "everything" about it, just how to use it efficiently to solve real problems. Best-selling author Michael Hartl gets you started writing practical and modern Python programs as fast as possible, with a focus on the real tools used every day by software developers. You'll learn how to use Python interactively, write shell scripts in it, use Python and a web framework to make simple dynamic web applications, and use Python libraries to do data science. Even if you're new to programming, Hartl helps you quickly build technical sophistication as you gain a solid understanding of object-oriented and functional programming, develop and publish a Python web application with the Flask framework. Focused exercises help you internalize what matters, without wasting time on details pros don't care about. Soon, it'll be like you were born knowing this stuff--and you'll be suddenly, seriously dangerous. About the Instructor Michael Hartl is the creator of the Python on Rails Tutorial, one of the leading introductions to web development, and is cofounder and principal author at Learn Enough. Previously, he was a physics instructor at the California Institute of Technology (Caltech), where he received a Lifetime Achievement Award for Excellence in Teaching. He is a graduate of Harvard College, has a Ph.D. in Physics from Caltech, and is an alumnus of the Y Combinator entrepreneur program. Skill Level Beginner to intermediate Learn How To Create a simple "hello, world" program using several different techniques Deploy a simple dynamic Python application to the web Use strings, arrays, and other native objects Define functions Use Python for functional and object-oriented programming Utilize test-driven development Write a shell script Develop a full Python web application for detecting palindromes Who Should Take This Course New and experienced developers looking for a practical introduction to Python. Course Requirements The only prerequisites are a familiarity with basic developer tools (command line, text editor, and Git) and beginning HTML Some programming experience is useful but not required Lesson Descriptions Lesson 1: Hello World! Lesson 1 begins at the beginning by having you create four simple "hello, world" programs using several different techniques. The main purpose of the "hello, world" is to make sure your system is correctly configured to execute the simple program that prints the string "hello, world!" to the screen. You start by writing a series of programs to display a greeting at a command line terminal, first in a REPL, then from a file, and then from a shell script. Finally, you write and deploy a simple proof-of-concept web application using the Flask web framework. Lesson 2: Strings Lesson 2 covers strings, probably the most important data structure on the Web since Web pages ultimately consist of strings and characters sent to and from the browser. Many other kinds of programs require string manipulation as well. As a result, strings make a great place to start your Python programming journey. The lesson starts with what strings are and how to create them. You then learn how to join, or concatenate, multiple string into a single string. Then you learn how to insert or interpolate one string into another. Next you learn how to print strings to the screen from the terminal window. As part of this, you see your first examples of Python Boolean variables and control flow. Finally, you learn how to iterate over strings with for loops, enabling you to access strings one character at a time. Lesson 3 : Lists In Lesson 2, you learned that strings can be thought of sequences of characters in a particular order. In Lesson 3, you learn about the list data type, which is the general Python container for arbitrary elements in a particular order. You start by explicitly connecting strings and lists via the string split method, and then you learn about various list methods throughout the rest of the lesson. After learning to split strings, you learn how to access elements in the resulting list, discovering that the same syntax works on strings, further deepening the connection between the two data types. Next you learn a variety of additional list methods beginning with selecting both single elements and multiple elements at once using list slicing, including the useful range datatype, and a clever technique using negative indices to select the last element in a list. Then you learn how to sort lists, which, if you have ever written a sorting algorithm by hand, you will find Python makes it ridiculously easy. You also learn how to reverse lists, a capability you will put to good use later on in the tutorial when learning to detect palindromes. Next you will learn how to add and remove list elements using append and pop. You then learn how to undo a string split using a list join, which includes an introduction to an important technique known as generator comprehension. Next, you learn how to iterate through lists using the same kind of for loop covered in Lesson in 2, which is valuable preparation for more advanced techniques covered in Lesson 6. Finally, you learn about two data types closely related to lists: tuples, which are essentially immutable lists, and sets, which can be thought of as a list of elements where repeat elements are ignored and the order doesn't matter. Lesson 4: Other Native Objects Now that we have taken a look at strings and arrays, Lesson 4 continues with a tour of some other important Python objects, which will give you a chance to learn about math, dates, regular expressions, and dictionaries. Like most programming languages, Python supports a large number of mathematical operations right out of the box, such as addition, subtraction, multiplication, and division. It also includes a math library, so you learn about more advanced operations such as logarithms and trigonometric functions. You also see an example of a personal triumph of mine, the inclusion of the circle constant Ï⁴ (tau), to find us the ratio of a circle's circumference to its radius, which Michael first proposed in 2010 and which was added to Python's standard math library in 2017. You also learn how to deal with times and dates in Python, such as getting the year, the day, or the exact time. Next you get an introduction in the powerful subject of regular expressions, which were discussed briefly in Learn Enough Developer Tools to Be Dangerous in the context of text editors and the grep command. Often called regexes for short, regular expressions are a powerful mini-language for matching patterns in text. You learn how to use regexes to quickly search strings for things like five digits in a row, thereby matching standard United States ZIP codes. The lesson ends with an introduction to dictionaries in Python. You use such objects, often referred to as hashes or associative arrays in other languages, are defined by key-value pairs, and in many ways behave like lists with strings, or sometimes other objects, instead of integers as indices. You apply this important object type to write your first substantial Python program, a shell script to count the unique words in a text. Lesson 5: Functions and Iterators So far in this tutorial, Python functions have been mentioned repeatedly, and and in Lesson 5 you finally learn to define functions of your own. The resulting ability gives us greater flexibility as programmers. We begin your study of functions in the read-eval-print loop, that is, the REPL, and then you learn how to put your function definitions in a file for use in a simple Flask web application. The lesson ends with a discussion of iterators, which are a powerful Python object type that represents a stream of data. The lesson pays particular attention to generators, probably the most common type of Python iterator. You will use a generator to make a first definition of an ispalindrome function, to see if a string is the same forward and backward. Lesson 6: Functional Programming Having learned how to define functions and apply them in a couple of different contexts. In Lesson 6, you take your programming to the next level by learning the basics of functional programming, a style of programming that emphasizes, you guessed it, functions. As you will see, functional programming in Python frequently employs a powerful and very Pythonic class of techn...
    Anmerkung: Online resource; title from title details screen (O'Reilly, viewed March 21, 2023)
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  • 8
    Online-Ressource
    Online-Ressource
    [Place of publication not identified] : Addison-Wesley Professional
    ISBN: 9780138092818 , 0138092818
    Sprache: Englisch
    Seiten: 1 online resource (1 video file (16 hr., 6 min.)) , sound, color.
    Ausgabe: [First edition].
    Serie: Live lessons
    DDC: 006.3/1
    Schlagwort(e): Machine learning ; Python (Computer program language) ; Instructional films ; Nonfiction films ; Internet videos
    Kurzfassung: Overview 12+ of Video Instruction Machine Learning in Python for Everyone video collection is based on three video courses that teach everything about the foundations and tools for machine learning. As machine learning has moved from futuristic AI projects to data analysis on your desk, you need to begin to build models and start coding machine learning tasks. This master class includes the following courses: Machine Learning with Python for Everyone Part 1: Learning Foundations, 2nd Edition Machine Learning with Python for Everyone, Part 2: Measuring Models Machine Learning with Python for Everyone, Part 3: Fundamental Toolbox Machine Learning with Python for Everyone Part 1: Learning Foundations is code-along sessions moving you from introductory machine learning concepts to concrete code. These videos skew away from heavy mathematics and focus on using Python, scikit-learn. Our emphasis on stories, graphics and code builds your understanding of machine learning. You learn how to load and explore simple datasets; build, train, and perform basic learning evaluation for a few models; compare the resource usage of different models in code snippets and scripts; and briefly explore some of the software and mathematics behind these techniques. Machine Learning with Python for Everyone, Part 2: Measuring Models teaches the fundamental metrics used to evaluate general learning systems and specific metrics used in classification and regression. You learn techniques for getting the most informative learning performance measures out of your data. You come away with a strong toolbox of numerical and graphical techniques to understand how your learning system will perform on novel data. Machine Learning with Python for Everyone, Part 3: Fundamental Toolbox teaches about fundamental classification and regression metrics like decision tree classifiers and regressors, support vector classifiers and regression, logistic regression, penalized regression, and discriminant analysis. You learn techniques for feature engineering, including scaling, discretization, and interactions. Finally, you tackle implementing pipelines for more complex processing and nested cross-validation for tuning hyperparameters. About the Instructor Dr. Mark Fenner , owner of Fenner Training and Consulting, LLC, has taught computing and mathematics to diverse adult audiences since 1999, and holds a PhD in computer science. His research has included design, implementation, and performance of machine learning and numerical algorithms; developing learning systems to detect user anomalies; and probabilistic modeling of protein function. About Pearson Video Training Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Prentice Hall, Sams, and Que Topics include: IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more. Learn more about Pearson Video training at http://www.informit.com/video.
    Anmerkung: Online resource; title from title details screen (O'Reilly, viewed February 20, 2023)
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  • 9
    Online-Ressource
    Online-Ressource
    [Place of publication not identified] : Addison-Wesley Professional
    ISBN: 9780137872558 , 0137872550
    Sprache: Englisch
    Seiten: 1 online resource (1 video file (5 hr., 4 min.)) , sound, color.
    Ausgabe: [First edition].
    Serie: Live lessons
    DDC: 004.1
    Schlagwort(e): Quantum computing ; Instructional films ; Nonfiction films ; Internet videos
    Kurzfassung: An 8-Hour Introduction to Quantum Computing from Dr. Chuck Easttom Quantum computing is fast approaching a practical reality. QC impacts the future of computing as well as security issues. QC will render current asymmetric cryptographic methods insecure, and that requires QC-resistant algorithms. IT personnel and cybersecurity professionals must have at least a basic conceptual understanding of quantum computing. This video course Clearly explains core concepts, terminology, and techniques Covers the foundational physics, math, and information theory you need Provides hands-on practice with quantum programming This is the perfect beginner's guide for anyone interested in a quantum computing career. Dr. Chuck Easttom brings together complete coverage of basic quantum computing concepts, terminology, and issues, along with key skills to get you started. This dynamic video course draws on 30+ years of experience from Dr. Easttom as a computer science instructor, consultant, and researcher. Dr. Easttom demystifies the fields underlying technical concepts and math, shows how quantum computing systems are designed and built, explains their implications for cybersecurity, and previews advances in quantum-resistant cryptography. This video course is designed to clearly and simply introduce two of today's leading quantum programming languages, Microsoft Q# and QASM, and guides you through sample projects. Throughout, tests, projects, and review questions help you deepen and apply your knowledge. Whether you're a student, professional, or manager, this video course will prepare you for the quantum computing revolution--and expand your career options, too. Master the linear algebra and other mathematical skills you'll need Explore key physics ideas, such as quantum states and uncertainty Review data structures, algorithms, and computing complexity Work with probability and set theory in quantum computing Familiarize yourself with basic quantum theory and formulae Understand quantum entanglement and quantum key distribution Discover how quantum computers are architected and built Explore several leading quantum algorithms Compare quantum and conventional asymmetric algorithms See how quantum computing might break traditional cryptography Discover several approaches to quantum-resistant cryptography Start coding with Q#, Microsoft's quantum programming language Simulate quantum gates and algorithms with QASM If you prefer a multimodal approach to learning, check out the Quantum Computing Fundamentals book by Chuck Easttom!.
    Anmerkung: Online resource; title from title details screen (O'Reilly, viewed February 20, 2023)
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