A Practical Approach for Machine Learning and Deep Learning Algorithms

Pandey, Abhishek Kumar

ISBN 10: 9388511131 / ISBN 13: 9789388511131

Verlag: BPB Publications 2019-09, 2019

Beschreibung

Bestandsnummer des Verkäufers 6666-IUK-9789388511131

Bibliografische Details

• Titel: A Practical Approach for Machine Learning and Deep Learning Algorithms
• Verlag: BPB Publications 2019-09
• Erscheinungsjahr: 2019
• Sprache: Englisch
• ISBN-10: 9388511131
• ISBN-13: 9789388511131
• Einband: PF
• Zustand: New

Über diesen Titel

Inhaltsangabe

Get Involved with Machine learning

Key Features

Machine learning in MATLAB using basic concepts and algorithms.

Algorithms of machine learning in a simple language using MATLAB code.

Deriving and accessing of data in MATLAB and next, pre-processing and preparation of data.

Machine learning workflow for health monitoring.

The neural network domain and implementation in MATLAB with explicit explanation of code and results.

How predictive model can be improved using MATLAB?

MATLAB code for an algorithm implementation, rather than for mathematical formula.

Machine learning workflow for health monitoring.

Description
Machine learning is mostly sought in the research field and has become an integral part of many research projects nowadays including commercial applications, as well as academic research. Application of machine learning ranges from finding friends on social networking sites to medical diagnosis and even satellite processing. In this book, we have made an honest effort to make the concepts of machine learning easy and give basic programs in MATLAB right from the installation part. Although the real-time application of machine learning is endless, however, the basic concepts and algorithms are discussed using MATLAB language so that not only graduation students but also researchers are benefitted from it.

What you will learn

Pre-requisites to machine learning

Finding natural patterns in data

Building classification methods

Data pre-processing in Python

Building regression models

Creating neural networks

Deep learning

Who This Book is For
The book is basically meant for graduate and research students who find the algorithms of machine learning difficult to implement. We have touched all basic algorithms of machine learning in detail with a practical approach. Primarily, beginners will find this book more effective as the chapters are subdivided in a manner that they find the building and implementation of algorithms in MATLAB interesting and easy at the same time.

Table of Contents

An Introduction to Machine Learning

Finding Natural Patterns in Data

Building Classification Methods

Data Pre – processing in Python

Building Regression Models

Creating Neural Networks

Introduction to Deep Learning

About the Author
Abhishek Kumar Pandey is pursuing his Doctorate in computer science and done M.Tech in Computer Sci. & Engineering. He has been working as an Assistant professor of Computer Science at Aryabhatt Engineering College and Research center, Ajmer and also visiting faculty in Government University MDS Ajmer.

Pramod Singh Rathore is pursuing his doctorate in Computer Science & engineering and done M. Tech. He has been working as the Assistant professor of Computer Science at Aryabhatt Engineering College and Research centre, Ajmer and visiting faculty in Government University MDS Ajmer.

Dr S. Balamurugan is the Head of Research and Development, Quants IS & CS, India. Formely, he was the Director of Research and Development at Mindnotix Technologies, India. He has authored/co-authored 33 books and has 200 publications in various international journals and conferences to his credit.