Machine Learning for Absolute Beginners

Machine Learning for Absolute Beginners is a comprehensive and beginner-friendly guide to understanding the fundamentals of machine learning. The book provides an easy-to-follow introduction to the basics of machine learning and covers various topics such as:

Supervised and unsupervised learning,
Deep learning,
Neural networks
Evaluation techniques

The author has used plain language and examples that are easy to understand, making it accessible for beginners who have little to no prior experience in machine learning.

The book is also supported by visual aids and practical exercises that help readers gain hands-on experience in using machine learning algorithms and techniques.

Readers will learn how to prepare data, select appropriate algorithms, train models, and evaluate their performance.

The book also includes real-world examples and case studies to help readers understand how machine learning is being used in various industries such as healthcare, finance, and e-commerce.Overall, "Machine Learning for Absolute Beginners" is an excellent resource for those who are new to machine learning and want to learn the basics of this fascinating field.

Table of Contents:

Machine Learning for Absolute Beginners
I | Introduction to Machine Learning | What is Machine Learning?
Types of Machine Learning
II | Supervised Learning | What is Supervised Learning?
Regression about Supervised Learning
Classification
III | Unsupervised Learning | What is Unsupervised Learning?
IV | Reinforcement Learning
Applications of Reinforcement Learning
V | Machine Learning Tools | Python Libraries for Machine Learning
VI | Machine Learning Ethics | Importance of Ethical Considerations in Machine Learning
Privacy and Security in Machine Learning
VII | Conclusion | Recap of Machine Learning Fundamentals
Final Thoughts for Absolute Beginners

Hours to read: 0 - 1
Total words: 12k