Decision Trees and Random Forests: A Visual Introduction For Beginners: A Simple Guide to Machine Learning with Decision Trees

If you want to learn how decision trees and random forests work, plus create your own, this visual book is for you. 

The fact is, decision tree and random forest algorithms are powerful and likely touch your life everyday.

From online search to product development and credit scoring, both types of algorithms are at work behind the scenes in many modern applications and services.

They are also used in countless industries such as medicine, manufacturing and finance to help companies make better decisions and reduce risk.

Whether coded or scratched out by hand, both algorithms are powerful tools that can make a significant impact.

This book is a visual introduction for beginners that unpacks the fundamentals of decision trees and random forests. If you want to dig into the basics with a visual twist plus create your own machine learning algorithms in Python, this book is for you.

• Bayes' Theorem Examples: A Visual Introduction For Beginners
• The Math of Neural Networks
• Machine Learning with Neural Networks: An In-depth Visual Introduction with Python: Make Your Own Neural Network in Python: A Simple Guide on Machine Learning with Neural Networks.
• Machine Learning With Random Forests And Decision Trees: A Visual Guide For Beginners
• Linear Regression And Correlation: A Beginner's Guide
• Hypothesis Testing: A Visual Introduction To Statistical Significance
• Numsense! Data Science for the Layman: No Math Added
• Probability - A Beginner's Guide To Permutations And Combinations: The Classic Equations, Better Explained
• Machine Learning For Absolute Beginners: A Plain English Introduction (Second Edition) (Machine Learning For Beginners Book 1)
• Algorithms Illuminated (Part 2): Graph Algorithms and Data Structures