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.

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.

As its title suggests, this innovative book has been written for life scientists needing to analyse their data sets, and programmers, wanting a better understanding of the types of experimental images life scientists investigate on a regular basis. Each chapter presents one self-contained biomedical experiment to be analysed. Part I of the book presents its two basic ingredients: essential concepts of image analysis and Matlab. In Part II, algorithms and techniques are shown as series of "recipes" or solved examples that show how specific techniques are applied to a biomedical experiments like Western Blots, Histology, Scratch Wound Assays and Fluoresence. Each recipe begins with simple techniques that gradually advance in complexity. Part III presents some advanced techniques for the generation of publication quality figures. The book does not assume any computational or mathematical expertise. A practical, clearly-written introduction to biomedical image analysis that provides the tools for life scientists and engineers to use when solving problems in their own laboratories. Presents the basic concepts of MATLAB software and uses it throughout to show how it can execute flexible and powerful image analysis programs tailored to the specific needs of the problem. Within the context of four biomedical cases, it shows algorithms and techniques as series of "recipes", or solved examples that show how a particular technique is applied in a specific experiment. Companion website containing example datasets, MATLAB files and figures from the book.

Go from total MATLAB newbie to plotting graphs and solving equations in a flash! MATLAB is one of the most powerful and commonly used tools in the STEM field. But did you know it doesn’t take an advanced degree or a ton of computer experience to learn it? MATLAB For Dummies is the roadmap you’ve been looking for to simplify and explain this feature-filled tool. This handy reference walks you through every step of the way as you learn the MATLAB language and environment inside-and-out. Starting with straightforward basics before moving on to more advanced material like Live Functions and Live Scripts, this easy-to-read guide shows you how to make your way around MATLAB with screenshots and newly updated procedures. It includes: A comprehensive introduction to installing MATLAB, using its interface, and creating and saving your first file Fully updated to include the 2020 and 2021 updates to MATLAB, with all-new screenshots and up-to-date procedures Enhanced debugging procedures and use of the Symbolic Math Toolbox Brand new instruction on working with Live Scripts and Live Functions, designing classes, creating apps, and building projects Intuitive walkthroughs for MATLAB’s advanced features, including importing and exporting data and publishing your work Perfect for STEM students and new professionals ready to master one of the most powerful tools in the fields of engineering, mathematics, and computing, MATLAB For Dummies is the simplest way to go from complete newbie to power user faster than you would have thought possible.

Highlighting the new aspects of MATLAB 7.10 and expanding on many existing features, this eighth edition continues to offer a hands-on, step-by-step introduction to using the powerful tools of MATLAB. It includes a new chapter on object-oriented programming, a new discussion of the MATLAB File Exchange window, major changes to the MATLAB Editor, and an explanation of more powerful Help tools. It also presents a synopsis of the most frequently used functions, operators, and special characters-providing quick and easy access to frequently used information. M-files and MEX-files for large examples are available at www.crcpress.com

MATLAB is one of the most widely used tools in the field of engineering today. Its broad appeal lies in its interactive environment with hundreds of built-in functions. This book is designed to get you up and running in just a few hours.

This book is designed for undergraduate students, completely new to programming with MATLAB. Case studies and examples are used extensively throughout this book and are at the core of what makes this book so unique. The author believes that the best way to learn MATLAB is to study programs written by experienced programmers and that the quality of these example programs determines the quality of the book. The examples in this book are carefully designed to teach you MATLAB programming as well as to inspire within you your own problem solving potential. Most of the examples used in this book are designed to solve a whole class of problems, rather than a single, specific problem. A learn by doing teaching approach is used all through the book. You are guided to tackle a problem using MATLAB commands first and then the commands are explained line by line. This process of learning through hands on experience is one of the most efficient and pain-free ways of learning MATLAB. This approach, together with the extensive use of ordered textboxes, figures, and tables, greatly reduces the size of the book, while still providing you with a book that’s comprehensive and easy to follow. The first chapter of this book introduces the MATLAB programming environment and familiarizes you with MATLAB’s core functionality. Chapters two through nine discuss basic MATLAB functionalities in a progressive and comprehensive way. The chapters start out simple and build in complexity as you advance through the book. Chapters ten through thirteen cover advanced topics that are particularly useful in college programs. Each chapter consists of sections, each covering a topic and providing one or more examples. Related MATLAB functions are organized at the end of a section. Additional exercise problems are provided at the end of chapters two through nine. Examples in each section are presented in a consistent way. An example is usually described first, followed by a MATLAB script. Any resulting text and graphics output (and in some cases inputs) that are produced from running a script are presented and discussed. Finally, the remainder of each section is devoted to explaining the purpose of the lines of the script.

A handbook for MATLAB which gives a focused approach to the software for students and professional researchers.

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.

This book is designed for undergraduate students completely new to programming with MATLAB. Case studies and examples are used extensively throughout this book and are at the core of what makes this book so unique. The author believes that the best way to learn MATLAB is to study programs written by experienced programmers and that the quality of these example programs determines the quality of the book. The examples in this book are carefully designed to teach you MATLAB programming as well as to inspire within you your own problem solving potential. Most of the examples used in this book are designed to solve a whole class of problems, rather than a single, specific problem. A learn by doing teaching approach is used all through the book. You are guided to tackle a problem using MATLAB commands first and then the commands are explained line by line. This process of learning through hands on experience is one of the most efficient and pain-free ways of learning MATLAB. This approach, together with the extensive use of ordered textboxes, figures, and tables, greatly reduces the size of the book, while still providing you with a book that’s comprehensive and easy to follow. The first chapter of this book introduces the MATLAB programming environment and familiarizes you with MATLAB’s core functionality. Chapters two through nine discuss basic MATLAB functionalities in a progressive and comprehensive way. The chapters start out simple and build in complexity as you advance through the book. Chapters ten through thirteen cover advanced topics that are particularly useful in college programs. Each chapter consists of sections, each covering a topic and providing one or more examples. Related MATLAB functions are organized at the end of a section. Additional exercise problems are provided at the end of chapters two through nine. Examples in each section are presented in a consistent way. An example is usually described first, followed by a MATLAB script. Any resulting text and graphics output (and in some cases inputs) that are produced from running a script are presented and discussed. Finally, the remainder of each section is devoted to explaining the purpose of the lines of the script. Who this book is for This book is developed mainly for undergraduate engineering students. It may be used in courses such as Computers in Engineering, or others that use MATLAB as a software platform. It can also be used as a self-study book for learning MATLAB. College level engineering examples are used in this book. Background knowledge for these engineering examples is illustrated as thoroughly as possible.