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  • 1
    Online Resource
    Online Resource
    MATLAB machine learning recipes : a problem-solution approach (2019)
    [California] : Apress
    Details
    ISBN: 9781484239162
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: MATLAB ; Machine learning ; Electronic books ; local ; Electronic books
    Abstract: Harness the power of MATLAB to resolve a wide range of machine learning challenges. This book provides a series of examples of technologies critical to machine learning. Each example solves a real-world problem. All code in MATLAB Machine Learning Recipes: A Problem-Solution Approach is executable. The toolbox that the code uses provides a complete set of functions needed to implement all aspects of machine learning. Authors Michael Paluszek and Stephanie Thomas show how all of these technologies allow the reader to build sophisticated applications to solve problems with pattern recognition, autonomous driving, expert systems, and much more. What you'll learn: How to write code for machine learning, adaptive control and estimation using MATLAB How these three areas complement each other How these three areas are needed for robust machine learning applications How to use MATLAB graphics and visualization tools for machine learning How to code real world examples in MATLAB for major applications of machine learning in big data Who is this book for: The primary audiences are engineers, data scientists and students wanting a comprehensive and code cookbook rich in examples on machine learning using MATLAB.
    Note: Includes bibliographical references. - Description based on online resource; title from cover (Safari, viewed June 7, 2019)
    URL: lizenzpflichtig
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  • 2
    Online Resource
    Online Resource
    MATLAB machine learning (2017)
    [Place of publication not identified] : Apress
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: MATLAB ; Machine learning ; Neural networks (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: This book is a comprehensive guide to machine learning with worked examples in MATLAB. It starts with an overview of the history of Artificial Intelligence and automatic control and how the field of machine learning grew from these. It provides descriptions of all major areas in machine learning. The book reviews commercially available packages for machine learning and shows how they fit into the field. The book then shows how MATLAB can be used to solve machine learning problems and how MATLAB graphics can enhance the programmer's understanding of the results and help users of their software grasp the results. Machine Learning can be very mathematical. The mathematics for each area is introduced in a clear and concise form so that even casual readers can understand the math. Readers from all areas of engineering will see connections to what they know and will learn new technology. The book then provides complete solutions in MATLAB for several important problems in machine learning including face identification, autonomous driving, and data classification. Full source code is provided for all of the examples and applications in the book. What you'll learn: An overview of the field of machine learning Commercial and open source packages in MATLAB How to use MATLAB for programming and building machine learning applications MATLAB graphics for machine learning Practical real world examples in MATLAB for major applications of machine learning in big data Who is this book for: The primary audiences are engineers and engineering students wanting a comprehensive and practical introduction to machine learning.
    Note: Includes bibliographical references. - Description based on online resource; title from cover (Safari, viewed November 9, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781484222508/?ar
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    Online Resource
    Online Resource
    MATLAB recipes : a problem-solution approach (2015)
    [New York] : Apress
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations.
    Series Statement: The expert's voice in MATLAB
    Keywords: MATLAB ; Engineering mathematics ; Data processing ; Electronic books ; Electronic books ; local
    Abstract: Learn from state-of-the-art examples in robotics, motors, detection filters, chemical processes, aircraft, and spacecraft. This is a practical reference for industry engineers using MATLAB to solve everyday problems. With MATLAB Recipes: A Problem-Solution Approach you will review contemporary MATLAB coding including the latest language features and use MATLAB as a software development environment including code organization, GUI development, and algorithm design and testing. This book provides practical guidance for using MATLAB to build a body of code you can turn to time and again for solving technical problems in your line of work. Develop algorithms, test them, visualize the results, and pass the code along to others to create a functional code base for your firm.
    Note: Description based on online resource; title from cover (Safari, viewed October 27, 2016)
    URL: https://learning.oreilly.com/library/view/-/9781484205594/?ar
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  • 4
    Online Resource
    Online Resource
    Practical MATLAB Deep Learning : A Project-Based Approach (2020)
    [Erscheinungsort nicht ermittelbar] : Apress | Boston, MA : Safari
    Details
    ISBN: 9781484251249
    Language: English
    Pages: 1 online resource (260 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local ; Electronic books
    Abstract: Harness the power of MATLAB for deep-learning challenges. This book provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. You'll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. Along the way, you'll learn to model complex systems, including the stock market, natural language, and angles-only orbit determination. You'll cover dynamics and control, and integrate deep-learning algorithms and approaches using MATLAB. You'll also apply deep learning to aircraft navigation using images. Finally, you'll carry out classification of ballet pirouettes using an inertial measurement unit to experiment with MATLAB's hardware capabilities. What You Will Learn Explore deep learning using MATLAB and compare it to algorithms Write a deep learning function in MATLAB and train it with examples Use MATLAB toolboxes related to deep learning Implement tokamak disruption prediction Who This Book Is For Engineers, data scientists, and students wanting a book rich in examples on deep learning using MATLAB.
    Note: Online resource; Title from title page (viewed February 7, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 5
    Online Resource
    Online Resource
    MATLAB Recipes : A Problem-Solution Approach (2021)
    [Erscheinungsort nicht ermittelbar] : Apress | Boston, MA : Safari
    Details
    ISBN: 9781484261248
    Language: English
    Pages: 1 online resource (423 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local ; Electronic books
    Abstract: Learn from state-of-the-art examples in robotics, motors, detection filters, chemical processes, aircraft, and spacecraft. With this book you will review contemporary MATLAB coding including the latest MATLAB language features and use MATLAB as a software development environment including code organization, GUI development, and algorithm design and testing. Features now covered include the new graph and digraph classes for charts and networks; interactive documents that combine text, code, and output; a new development environment for building apps; locally defined functions in scripts; automatic expansion of dimensions; tall arrays for big data; the new string type; new functions to encode/decode JSON; handling non-English languages; the new class architecture; the Mocking framework; an engine API for Java; the cloud-based MATLAB desktop; the memoize function; and heatmap charts. MATLAB Recipes: A Problem-Solution Approach, Second Edition provides practical, hands-on code snippets and guidance for using MATLAB to build a body of code you can turn to time and again for solving technical problems in your work. Develop algorithms, test them, visualize the results, and pass the code along to others to create a functional code base for your firm. What You Will Learn Get up to date with the latest MATLAB up to and including MATLAB 2020b Code in MATLAB Write applications in MATLAB Build your own toolbox of MATLAB code to increase your efficiency and effectiveness Who This Book Is For Engineers, data scientists, and students wanting a book rich in examples using MATLAB.
    Note: Online resource; Title from title page (viewed February 2, 2021) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 6
    Online Resource
    Online Resource
    Practical MATLAB deep learning : a projects-based approach (2022)
    New York, NY : Apress
    Details
    ISBN: 9781484279120 , 1484279123
    Language: English
    Pages: 1 online resource (338 pages) , illustrations
    Edition: Second edition.
    Parallel Title: Erscheint auch als
    Keywords: MATLAB ; Machine learning ; Electronic books
    Abstract: Harness the power of MATLAB for deep-learning challenges. Practical MATLAB Deep Learning, Second Edition, remains a one-of a-kind book that provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. In this book, you’ll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. This edition includes new and expanded projects, and covers generative deep learning and reinforcement learning.
    Note: Includes bibliographical references and index
    URL: lizenzpflichtig
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  • 7
    Online Resource
    Online Resource
    MATLAB Machine Learning Recipes : A Problem-Solution Approach (2024)
    Berkeley, CA : Apress L. P.
    Details
    ISBN: 9781484298466 , 1484298462
    Language: English
    Pages: 1 online resource (458 p.)
    Edition: 3rd ed.
    Parallel Title: Erscheint auch als
    Keywords: MATLAB ; Machine learning ; Apprentissage automatique
    Abstract: Harness the power of MATLAB to resolve a wide range of machine learning challenges. This new and updated third edition provides examples of technologies critical to machine learning. Each example solves a real-world problem, and all code provided is executable. You can easily look up a particular problem and follow the steps in the solution. This book has something for everyone interested in machine learning. It also has material that will allow those with an interest in other technology areas to see how machine learning and MATLAB can help them solve problems in their areas of expertise. The chapter on data representation and MATLAB graphics includes new data types and additional graphics. Chapters on fuzzy logic, simple neural nets, and autonomous driving have new examples added. And there is a new chapter on spacecraft attitude determination using neural nets. Authors Michael Paluszek and Stephanie Thomas show how all of these technologies allow you to build sophisticated applications to solve problems with pattern recognition, autonomous driving, expert systems, and much more. What You Will Learn Write code for machine learning, adaptive control, and estimation using MATLAB Use MATLAB graphics and visualization tools for machine learning Become familiar with neural nets Build expert systems Understand adaptive control Gain knowledge of Kalman Filters Who This Book Is For Software engineers, control engineers, university faculty, undergraduate and graduate students, hobbyists.
    Note: Description based upon print version of record. - 4.4 Using the UKF for State Estimation
    URL: lizenzpflichtig
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