Learn how to run Decisions Trees, Random Forest and Extreme Gradient Boost (XGB) machine learning models in Pythons. This is a full tutorial in machine learning. We start with the problem formulation phase, then EDA phase, then running and evaluating different models. We also show how to adjust the hyperparameters of the models. At the end, we show how to deploy the model predictions in Power BI.

Tutorial Overview:

  • What is the machine learning process
  • How to load raw data from excel to python and run ML
  • How to clean the raw data for machine learning (EDA)
  • How to split the raw data for machine learning
  • How to Run decision trees machine learning model
  • How to evaluate machine learning models
  • How to visualize the decision tree in Python
  • How to create a confusion matrix in Python

Git Repo:


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Decision Tree Algorithm in Machine Learning Python – Predicting Churn Example
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