Machine Learning Algorithms: Theory and Applications

Machine Learning Algorithms is for current and ambitious machine learning specialists looking to implement solutions to real-world machine learning problems. It talks entirely about the various applications of machine and deep learning techniques, with each chapter dealing with a novel approach of machine learning architecture for a specific application, and then compares the results with previous algorithms.

The book discusses many methods based in different fields, including statistics, pattern recognition, neural networks, artificial intelligence, sentiment analysis, control, and data mining, in order to present a unified treatment of machine learning problems and solutions. All learning algorithms are explained so that the user can easily move from the equations in the book to a computer program.

Mettu Srinivas PhD from the Indian Institute of Technology Hyderabad, and is currently an assistant professor in the Department of Computer Science and Engineering, NIT Warangal, India.

G. Sucharitha PhD from KL University, Vijayawada and is currently an assistant professor in the Department of Electronics and Communication Engineering at ICFAI Foundation for Higher Education Hyderabad.

Anjanna Matta PhD from the Indian Institute of Technology Hyderabad and is currently an assistant professor in the Department of Mathematics at ICFAI Foundation for Higher Education Hyderabad.

Prasenjit Chatterjee PhD is an associate professor in the Mechanical Engineering Department at MCKV Institute of Engineering, India.