One of the most potent algorithms in data science and machine learning is the decision tree algorithm. Data scientists and machine learning engineers utilise it a lot to address business problems and make things easy to understand for your customers. This book will explain decision trees to you and show you how to create one with Python.
Why educate oneself on decision trees? The most popular and often utilised machine learning algorithms are decision trees. Regression and classification difficulties can both be resolved with it.
Decision trees are widely applicable across various industries due to their ease of interpretation. In the book Getting Started with Decision Trees, what would you learn?
- Overview of Decision Trees
- Words used in relation to decision trees
- Various decision tree splitting criteria, such as chi-square, Gini, etc.
- Python implementation of a decision tree
What You'll Learn
- Basics of Decision Trees
- How to Apply Decision Trees to build Machine Learning models
- Building Decision Tree models in Python
- How to improve and optimise your decision tree models
