MACHINE LEARNING by Ms. Rahama Salman Dr. Subodhini Gupta Dr. Clara Shanthi D Mohammed Ashfaq Hussain Ms. Subuhi Kashif Ansari

This book aims to provide a broad MACHINE LEARNING for the importance of MACHINE LEARNING is well known in various engineering fields.
It provides a logical method of explaining various complicated concepts and stepwise methods to explain essential topics. Each chapter is well supported with the necessary illustrations. All the chapters in the book are arranged in a proper sequence that permits each topic to build upon earlier studies.
MACHINE LEARNING is a critical research area. The techniques developed in this area so far require to be summarized appropriately. In this book, the fundamental theories of these techniques are introduced.
The brief content of this book is as follows-
CHAPTER 1 FUNDAMENTAL
CHAPTER 2 SUPERVISED LEARNING
CHAPTER 3 BAYESIAN LEARNING
CHAPTER 4 UNSUPERVISED LEARNING
CHAPTER 5 NEURAL NETWORKS
CHAPTER 6 ENSEMBLE AND PROBABILISTIC LEARNING
CHAPTER 7 REINFORCEMENT LEARNING AND EVALUATING HYPOTHESES
CHAPTER 8 ANALYTICAL LEARNING
CHAPTER 9 GENETIC ALGORITHMS
CHAPTER 10 LEARNING SETS OF RULES
CHAPTER 11 APPLICATIONS & CASE STUDIES
ACRONYM
REFERENCES
This book is original in style and method. No pains have been spared to make it as compact, perfect, and reliable as possible. Every attempt has been made to make the book a unique one.
In particular, this book can be handy for practitioners and engineers interested in this area. Hopefully, the chapters presented in this book have just done that.