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Learning Matlab
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Book Synopsis MATLAB for Machine Learning by : Giuseppe Ciaburro
Download or read book MATLAB for Machine Learning written by Giuseppe Ciaburro and published by Packt Publishing Ltd. This book was released on 2017-08-28 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extract patterns and knowledge from your data in easy way using MATLAB About This Book Get your first steps into machine learning with the help of this easy-to-follow guide Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB Understand how your data works and identify hidden layers in the data with the power of machine learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well. What You Will Learn Learn the introductory concepts of machine learning. Discover different ways to transform data using SAS XPORT, import and export tools, Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data. Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment. Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures. Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox. Learn feature selection and extraction for dimensionality reduction leading to improved performance. In Detail MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You'll start by getting your system ready with t he MATLAB environment for machine learning and you'll see how to easily interact with the Matlab workspace. We'll then move on to data cleansing, mining and analyzing various data types in machine learning and you'll see how to display data values on a plot. Next, you'll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You'll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you'll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB. Style and approach The book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.
Book Synopsis Learning MATLAB by : Tobin A. Driscoll
Download or read book Learning MATLAB written by Tobin A. Driscoll and published by SIAM. This book was released on 2009-07-23 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: A handbook for MATLAB which gives a focused approach to the software for students and professional researchers.
Download or read book MATLAB Deep Learning written by Phil Kim and published by Apress. This book was released on 2017-06-15 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MATLAB Deep Learning employs MATLAB as the underlying programming language and tool for the examples and case studies in this book. With this book, you'll be able to tackle some of today's real world big data, smart bots, and other complex data problems. You’ll see how deep learning is a complex and more intelligent aspect of machine learning for modern smart data analysis and usage. What You'll Learn Use MATLAB for deep learning Discover neural networks and multi-layer neural networks Work with convolution and pooling layers Build a MNIST example with these layers Who This Book Is For Those who want to learn deep learning using MATLAB. Some MATLAB experience may be useful.
Book Synopsis Learning to Program with MATLAB by : Craig S. Lent
Download or read book Learning to Program with MATLAB written by Craig S. Lent and published by Wiley. This book was released on 2013-01-09 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: The text is for instructors who want to use MATLAB to teach introductory programming concepts. Since many students struggle with applying the concepts that underlie good programming practice, Learning to Program with MATLAB: Building GUI Tools was designed upon the observation that student learning is enhanced if the students themselves build the GUI (graphical user interface) tool, construct the computational model, implement the visualization of results, and design the GUI. This text teaches the core concepts of computer programming—arrays, loops, functions, and basic data structures—using MATLAB. The chapter sequence covers text-based programs, then programs that produce graphics, building up to an emphasis on GUI tools. This progression unleashes the real power of MATLAB—creating visual expressions of the underlying mathematics of a problem or design.
Download or read book Learning MATLAB written by Walter Gander and published by Springer. This book was released on 2015-11-21 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive and stimulating introduction to Matlab, a computer language now widely used for technical computing, is based on an introductory course held at Qian Weichang College, Shanghai University, in the fall of 2014. Teaching and learning a substantial programming language aren’t always straightforward tasks. Accordingly, this textbook is not meant to cover the whole range of this high-performance technical programming environment, but to motivate first- and second-year undergraduate students in mathematics and computer science to learn Matlab by studying representative problems, developing algorithms and programming them in Matlab. While several topics are taken from the field of scientific computing, the main emphasis is on programming. A wealth of examples are completely discussed and solved, allowing students to learn Matlab by doing: by solving problems, comparing approaches and assessing the proposed solutions.
Book Synopsis MATLAB: Easy Way of Learning by : S. SWAPNA KUMAR
Download or read book MATLAB: Easy Way of Learning written by S. SWAPNA KUMAR and published by PHI Learning Pvt. Ltd.. This book was released on 2016-01-30 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: MATLAB: Easy Way of Learning, covers exactly what students need to know in an introductory course. This comprehensive book helps reader in understanding all the aspects of MATLAB basics and applications in an easy way. The authors explain concepts by balanced treatment of theoretical and practical concepts with easy-to-understand programming codes and executions. The book is suitable for the postgraduate and undergraduate students of engineering and sciences streams.
Book Synopsis A First Course in Machine Learning by : Simon Rogers
Download or read book A First Course in Machine Learning written by Simon Rogers and published by CRC Press. This book was released on 2016-10-14 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces the main algorithms and ideas that underpin machine learning techniques and applications Keeps mathematical prerequisites to a minimum, providing mathematical explanations in comment boxes and highlighting important equations Covers modern machine learning research and techniques Includes three new chapters on Markov Chain Monte Carlo techniques, Classification and Regression with Gaussian Processes, and Dirichlet Process models Offers Python, R, and MATLAB code on accompanying website: http://www.dcs.gla.ac.uk/~srogers/firstcourseml/"
Download or read book MATLAB Primer written by Timothy A. Davis and published by CRC Press. This book was released on 2010-08-18 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Highlighting the new aspects of MATLAB 7.10 and expanding on many existing features, MATLAB Primer, Eighth Edition shows you how to solve problems in science, engineering, and mathematics. Now in its eighth edition, this popular primer continues to offer a hands-on, step-by-step introduction to using the powerful tools of MATLAB.New to the Eighth E
Book Synopsis MATLAB Machine Learning by : Michael Paluszek
Download or read book MATLAB Machine Learning written by Michael Paluszek and published by Apress. This book was released on 2016-12-28 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Practical MATLAB Deep Learning by : Michael Paluszek
Download or read book Practical MATLAB Deep Learning written by Michael Paluszek and published by Apress. This book was released on 2020-02-07 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 LearnExplore deep learning using MATLAB and compare it to algorithmsWrite a deep learning function in MATLAB and train it with examplesUse MATLAB toolboxes related to deep learningImplement tokamak disruption predictionWho This Book Is For Engineers, data scientists, and students wanting a book rich in examples on deep learning using MATLAB.
Book Synopsis Problem-Based Learning in Communication Systems Using MATLAB and Simulink by : Kwonhue Choi
Download or read book Problem-Based Learning in Communication Systems Using MATLAB and Simulink written by Kwonhue Choi and published by John Wiley & Sons. This book was released on 2016-02-29 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed to help teach and understand communication systems using a classroom-tested, active learning approach. Discusses communication concepts and algorithms, which are explained using simulation projects, accompanied by MATLAB and Simulink Provides step-by-step code exercises and instructions to implement execution sequences Includes a companion website that has MATLAB and Simulink model samples and templates (password: matlab)
Book Synopsis MATLAB® Essentials by : William Bober
Download or read book MATLAB® Essentials written by William Bober and published by CRC Press. This book was released on 2017-09-11 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: All disciplines of science and engineering use numerical methods for complex problem analysis, due to the highly mathematical nature of the field. Analytical methods alone are unable to solve many complex problems engineering students and professionals confront. Introduction to MATLAB® Programming for Engineers and Scientists examines the basic elements of code writing, and describes MATLAB® methods for solving common engineering problems and applications across the range of engineering disciplines. The text uses a class-tested learning approach and accessible two-color page design to guide students from basic programming to the skills needed for future coursework and engineering practice.
Book Synopsis From Shortest Paths to Reinforcement Learning by : Paolo Brandimarte
Download or read book From Shortest Paths to Reinforcement Learning written by Paolo Brandimarte and published by Springer Nature. This book was released on 2021-01-11 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic programming (DP) has a relevant history as a powerful and flexible optimization principle, but has a bad reputation as a computationally impractical tool. This book fills a gap between the statement of DP principles and their actual software implementation. Using MATLAB throughout, this tutorial gently gets the reader acquainted with DP and its potential applications, offering the possibility of actual experimentation and hands-on experience. The book assumes basic familiarity with probability and optimization, and is suitable to both practitioners and graduate students in engineering, applied mathematics, management, finance and economics.
Book Synopsis MATLAB Machine Learning Recipes by : Michael Paluszek
Download or read book MATLAB Machine Learning Recipes written by Michael Paluszek and published by Apress. This book was released on 2019-01-31 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis MATLAB Programming by : David C. Kuncicky
Download or read book MATLAB Programming written by David C. Kuncicky and published by Prentice Hall. This book was released on 2004 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aimed at undergraduate engineering students, this text starts with a basic introduction to MATLAB and works through its interactive environment, desktop, programming structures, arrays and matrices, procedural abstraction, object-oriented programming andmore.
Book Synopsis MATLAB for Engineers by : Holly Moore
Download or read book MATLAB for Engineers written by Holly Moore and published by Prentice Hall. This book was released on 2009 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt: MATLAB for Engineers, 2eis ideal for Freshman or Introductory courses in Engineering and Computer Science. With a hands-on approach and focus on problem solving, this introduction to the powerful MATLAB computing language is designed for students with only a basic college algebra background. Numerous examples are drawn from a range of engineering disciplines, demonstrating MATLAB’s applications to a broad variety of problems. Note: This book is included in Prentice Hall’sESource series. ESource allows professors to select the content appropriate for their freshman/first-year engineering course. Professors can adopt the published manuals as is or use ESource’s websitewww.prenhall.com/esourceto view and select the chapters they need, in the sequence they want. The option to add their own material or copyrighted material from other publishers also exists.
Book Synopsis A Guide to MATLAB Object-Oriented Programming by : Andy H. Register
Download or read book A Guide to MATLAB Object-Oriented Programming written by Andy H. Register and published by CRC Press. This book was released on 2007-05-14 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Guide to MATLAB Object-Oriented Programming is the first book to deliver broad coverage of the documented and undocumented object-oriented features of MATLAB. Unlike the typical approach of other resources, this guide explains why each feature is important, demonstrates how each feature is used, and promotes an understanding of
