Machine Learning Algorithms Using Python Programming


Gaurav Patil (Author) – Department of Artificial Intelligence, G H Raisoni College of Engineering, Nagpur, India
Prateek Dutta (Author) – Department of Artificial Intelligence, G H Raisoni College of Engineering, Nagpur, India

Series: Internet of Things and Machine Learning

BISAC: COM094000

The machine learning field is concerned with the question of how to create computer programs that automatically improve information. In recent years, many successful electronic learning applications have been made, from data mining systems that learn to detect fraudulent credit card transactions, filtering programs that learn user readings, to private cars that learn to drive on public highways. At the same time, there have been significant developments in the concepts and algorithms that form the basis for this field. Machine learning is programming computers to optimize a performance criterion using example data or past experience.

The goal of this textbook is to present the key concepts of Machine Learning which includes Python concepts and Interpreter, Foundation of Machine Learning, Data Pre-processing, Supervised Machine Learning, Unsupervised Machine Learning, Reinforcement Learning, Kernel Machine, Design and analysis of Machine Learning experiment and Data visualization. The theoretical concepts along with coding implementation are covered. This book aims to pursue a middle ground between a theoretical textbook and one that focuses on applications. The book concentrates on the important ideas in machine learning.

Table of Contents


About the Author

Chapter 1. Python Concept & Interpreter

Chapter 2. Foundation of Machine Learning

Chapter 3. Data Preprocessing

Chapter 4. Supervised Learning

Chapter 5. Unsupervised Learning

Chapter 6. Reinforcement Learning

Chapter 7. Kernel Machine

Chapter 8. Data Visualization

Additional information


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