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Introduction

Machine Learning Concepts

🎥 Introducing machine-learning concepts
✅ Quiz Intro.01

The predictive modeling pipeline

Module overview
Tabular data exploration
Fitting a scikit-learn model on numerical data

Categorical data

Handling categorical data

Decision tree models

Module overview
Intuitions on tree-based models
- 🎥 Intuitions on tree-based models
- ✅ Quiz M5.01

Combining categorical and numerical data

Combining categorical and numerical data

Selecting the best model

Module overview
🎥 Overfitting and Underfitting
✅ Quiz M2.01
🎥 Comparing train and test errors
📝 Exercise M2.01
📃 Solution for Exercise M2.01

Advanced topics

Module overview
🎥 Advanced topics
Resources for learning about advanced topics

Concluding remarks

🎥 Concluding remarks
Concluding remarks

Appendix

Glossary
Datasets description
Acknowledgement
Notebook timings
Table of contents

Repository
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Handling categorical data

Handling categorical data#

Encoding of categorical variables
📝 Exercise M1.04
📃 Solution for Exercise M1.04
Using numerical and categorical variables together

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✅ Quiz M1.02

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Encoding of categorical variables

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