A Practical Approach for Machine Learning and Deep Learning Algorithms

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.

Tagline

Guide Covering Topics From Machine Learning, Regression Models, Neural Network To Tensor Flow

Key Features

* Machine Learning In Matlab Using Basic Concepts And Algorithms.
* 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.

What Will You 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.
n of code and results.

* How the predictive model can be improved using MATLAB?
* MATLAB code for an algorithm implementation, rather than for mathematical formula.
* Machine learning workflow for health monitoring.

1. Pre-requisite to Machine Learning
2. An introduction to Machine Learning
3. Finding Natural Patterns in Data
4. Building Classification Methods
5. Data Pre-Processing in Python
6. Building Regression Models
7. Creating Neural Networks
8. Introduction to Deep Learning

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. He has total Academic teaching experience of more than eight years with more than 50 publications in reputed National and International Journals. His research area includes- Artificial intelligence, Image processing, Computer Vision, Data Mining, Machine Learning. He has been in the International Conference Committee of many International conferences. He has been the reviewer for IEEE and Inder Science Journal. He has authored 4 books published internationally and 7 edited books.. He is also a member of various National and International professional societies in the field of engineering & research like Member of IAENG (International Association of Engineers), Associate Member of IRED (Institute of Research Engineers and Doctors), Associate Member of IAIP (International Association of Innovation Professionals), Member of ICSES (International Computer Science and Engineering Society), Life Member of ISRD (International Society for Research & Development), Member of ISOC (Internet Society). He has got Sir CV Raman lifetime achievement national award for 2018 in young researcher and faculty Category. He is serving as an Associate Editor of the Global Journal on Innovation, Opportunities, and Challenges in Applied Artificial Intelligence and Machine Learning.

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 center, Ajmer and visiting faculty in Government University MDS Ajmer. He has been edited and authored many books with Wiley, Taylor & Francis Eureka group, CRC USA. He has total Academic teaching experience of more than eight years with more than 40 publications as Research papers and Chapters in reputed National and International E-SCI SCOPUS. He has done five edited books. His research area includes machine learning, NS2, Computer Network, Mining, and DBMS. He has been serving in the editorial and advisory committee of the Global journal group, Eureka Group of Journals. He has been a member of various National and International professional societies in the field of engineering & research like Member of IAENG (International Association of Engineers).

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. He was awarded Three Post-Doctoral Degrees- Doctor of Science(D.Sc.) degree and Two Doctor of Letters(D.Litt) degrees for his significant contribution to research and development in Engineering and is the recipient of the Best Director Award, 2018. His biography is listed in “World Book of Researchers” 2018, Oxford, UK and in “Marquis WHO’S WHO” 2018 issue, New Jersey, USA. He carried out a healthcare consultancy project for VGM Hospitals between 2013 and 2016, and his current research projects include “Women Empowerment using IoT”, “Health-Aware Smart Chair”, “Advanced Brain Simulators for Assisting Physiological Medicine”, “Designing Novel Health Bands” and “IoT -based Devices for Assisting Elderly People”. His professional activities include roles as Associate Editor, editorial board member and/or reviewer for more than 100 international journals and conferences. He has been an invited as Chief Guest/Resource Person/Keynote Plenary Speaker in many reputed Universities and Colleges His research interests include Augmented Reality, the Internet of Things, Big Data Analytics, Cloud Computing, and Wearable Computing. He is a life member of the ACM, ISTE, and CSI.
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