Summary:
The book serves as an introductory guide to machine learning, explaining fundamental concepts and algorithms in an accessible language without requiring a background in mathematics or programming. It covers data preprocessing, simple linear regression, and decision trees, among other topics, and includes practical examples and illustrations to help beginners understand and apply machine learning techniques.
Key points:
1. Machine Learning Basics: The book introduces machine learning, a part of artificial intelligence that lets computers learn from data. It explains supervised, unsupervised, and reinforcement learning, and the role of data in machine learning.
Books similar to "Machine Learning For Absolute Beginners":
![](/books/09/098972f94b.jpg)
Introduction to Machine Learning with Python
Andreas C. Müller|Sarah Guido
![](/books/b5/b586b26007.jpg)
Deep Learning with Python
Francois Chollet
![](/books/7e/7e6e24e435.jpg)
Data Science from Scratch
Joel Grus
![](/books/88/88920ee06d.jpg)
The Hundred-Page Machine Learning Book
Andriy Burkov
![](/books/b7/b71b22b679.jpg)
Predictive Analytics
Eric Siegel
![](/books/50/509c042bca.jpg)
Data Science
John D. Kelleher|Brendan Tierney
![](/books/67/6750eea136.jpg)
Practical Statistics for Data Scientists
Peter Bruce|Andrew Bruce|Peter Gedeck
![](/books/a7/a7e16173b9.jpg)
Artificial Intelligence
Melanie Mitchell
![](/books/0a/0aad0d3b4e.jpg)
Machine Learning With Random Forests And Decision Trees
Scott Hartshorn
![](/books/91/918e20026e.jpg)
Data Structure and Algorithmic Thinking with Python
Narasimha Karumanchi