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End-to-end Machine Learning: Decision trees, Build a transit time predictor in python
Created by Brandon Rohrer
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What you'll learn
- Build a decision tree from scratch.
- Tune a machine learning model's hyperparameters and evaluate its performance.
- Use Pandas DataFrames to manipulate data and make statistical computations.
- Create a custom model visualization using matplotlib.
- Use decision trees to make predictions.
- Build your own transit time predictor.
- Handle dates and times cleanly using python's datetime package.
- Save and restore data using python's pickle package.
- Programmatically dowload and parse data in a JSON format.
- Interpret command line arguments using python's argparse package.
Requirements
- It will help if you are already familiar with the basics of python.
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