BPB Publications, 2019 — 280 p. — ISBN: 978-93-88511-13-1.
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. Machine learning applications range 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 graduate students but also researchers are benefitted from it.
The book is meant for graduate and research students who find the algorithms of machine learning difficult to implement. We have touched all basic machine learning algorithms 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.
Get Involved with Machine LearningKey FeaturesMachine learning in MatLAB using basic concepts and algorithms.
Algorithms of machine learning in a simple language using MatLAB code.
Deriving and accessing 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 an explicit explanation of code and results.
How predictive model can be improved using MatLAB?
MatLAB code for an algorithm implementation, rather than for mathematical formulas.
Machine learning workflow for health monitoring.
DescriptionMachine 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. Machine learning applications range 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 graduate students but also researchers are benefitted from it.
What you will learnPre-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 ForThe book is meant for graduate and research students who find the algorithms of machine learning difficult to implement. We have touched all basic machine learning algorithms 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.
Abhishek Kumar Pandey is pursuing his Doctorate in computer science and has 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 at Government University MDS Ajmer.
Pramod Singh Rathore is pursuing his doctorate in Computer Science & Engineering and has done M. Tech. He has been working as the Assistant professor of Computer Science at Aryabhatt Engineering College and Research Center, Ajmer, and visiting faculty at Government University MDS Ajmer.
Dr S. Balamurugan is the Head of Research and Development, Quants IS & CS, India. Formerly, 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.