Fundamentals of Machine & Deep Learning: A Complete Guide on Python Coding for Machine and Deep Learning with Practical Exercises for Learners

This book is written to provide a solid foundation in machine learning using Python libraries by providing case studies and real-life examples. It covers topics such as the fundamentals of machine learning, the introduction to Python. It is intended for students studying machine learning in their Undergraduate and Post graduate courses in Information Technology, Computer Engineering, Electronics and Communications Engineering and Electrical Engineering. An introduction to a wide range of deep learning topics, covering conceptual and mathematical backgrounds, deep learning techniques used in industry, and research perspectives. The text provides conceptual and mathematical background, covering relevant concepts in linear algebra, probability theory, and information theory, number computing, and machine learning. It describes the deep learning techniques used by industry professionals, including deep feedback networks, regularization, optimization algorithms, convolution networks, and hands-on methodology. This text book “Fundamentals of Machine and Deep Learning” is organized into Ten Chapters.
Chapter -1: Machine Learning
Chapter-2: Machine Learning Algorithms
Chapter -3: Models of Machine Learning
Chapter-4: Artificial Intelligence and Machine Learning
Chapter 5: Mathematics & Python Programs for Machine Learning
Chapter- 6: Future Scope of Machine learning in Future
Chapter 7: Introduction of Deep Learning
Chapter-8: Models for Deep Learning
Chapter 9: Deep Learning Algorithms
Chapter- 10: Future Scope of Deep Learning

Salient Features Comprehensive Coverage of Machine Learning Algorithms, Models of Machine Learning, Artificial Intelligence and Machine Learning, Mathematics & Python Programs for Machine Learning and Future Scope of Machine learning in Future New elements in book include Deep Learning, Models for Deep Learning, Deep Learning Algorithms and Future Scope of Deep Learning. Clear perception of the various program using Python with a large number of neat, well drawn and illustrative diagrams. Simple Language, easy- to- understand manner.Our sincere thanks are due to all Scientists, Engineers, Authors and Publishers, whose works and text have been the source of enlightenment, inspiration and guidance to us in presenting this small book. I will appreciate any suggestions from students and faculty members alike so that we can strive to make the text book more useful in the edition to come.