Description
Machine learning and Machine Intelligence is a complete book to read and perform practical in computer labs. Just reading theory cannot make you perform the practical(S). The present book is the composition of both, for the convenience of the students. Many of the Degrees or Diplomas or Certification Programs are being conducted in Machine Learning and Machine Intelligence fields. But it has become difficult for software companies to separate chaff from the grain. This book is an excellent guide for aspiring Data Science professionals and a valuable resource bank to perform experiments in AIDS and AIML branches.
Salient Feature:
1. Includes numerous illustrative examples to understand and perform the practical easily.
2. Demonstrates every experiment in a systematic and good programming style.
3. Students of all branches- B.E/ B. Tech. in CSE/IT/ECE, B. Tech. in AIML Branch, B. Tech. In AIDS Branches as well as B. Tech in CS (DS) and CS (ML) branches will be benefitted from this art.
TABLE OF CONTENTS
Chapter 1: Introduction to Machine and Deep learning.
Chapter 2: Types of Learning.
Chapter 3: Classification Families.
Chapter 4: Learning Algorithms.
Chapter 5: Unsupervised Learning and their Algorithms.
Chapter 6: Reinforcement Learning and Control.
Chapter 7: IOT and Machine Learning.
Chapter 8: Project 1: Object Detection and Smudging Using Gradient Descent.
Chapter 9: Project 2: Spam Filtering based on Text Classification Using Machine Learning Algorithms.
Appendices-A: Glossary.
Appendices-B: Some Important Question for Revision.
Lab Manual of Machine Learning
Experiments
Suggested List of ML Projects
References
Index
Authors
Dr. Rajiv Chopra as Doctorate (Ph. D. Computer Science) in Computer Science from Banasthali VidyaPith University. Also he has M. Tech. (IT) from Guru Gobind Singh Indraprashta University, Delhi. He is MIT and BE in Computer Science Engineering.
The author has 30 books to his credit. He has published several research papers in Refereed International Journals and Refereed Conferences. Also the author is the life member of CSI, ISTE and CEGR. Also he is the reviewer of America Journal of AI.
The author is diligent, ebullient and inquisitive Associate Professor in department of Computer Science Engineering at GTBIT Delhi. He has more than 20 years of teaching experience. He has demonstrated great technical insight which exemplifies his profound knowledge of Computer Science. His innovative solutions to the problems, determination and work ethics are few of his attributes to endorse. His propensity to grasp the concepts of ML has simplified the book. The author has shown a right blend of aptitude, merit and determination.
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