02 - Linear and Logistic Regression: From Theory to Practice
Master the 2 most important ML algorithms: linear regression for numerical predictions and logistic…
03 - Decision Trees and Random Forest: Classification and Regression
Discover decision trees (interpretable, easy to understand) and random forests (ensemble of trees for better results). Learn how entropy works, how to build trees, overfitting issues, pruning, feature importance, and when to use them vs linear regression.
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Discover decision trees (interpretable, easy to understand) and random forests (ensemble of trees for better results). Learn how entropy works, how to build trees, overfitting issues, pruning, feature importance, and when to use them vs linear regression.
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See Also
Explore related series that complement this topic.
- Advanced Deep Learning and Neural NetworksDeep learning extends classical machine learning with deep neural networks for unstructured data.
- Intermediate Mathematics and Statistics for AILinear algebra, probability, and optimisation are the essential mathematical tools underpinning ML.
- Advanced MLOps and Machine Learning in ProductionMLOps takes ML models from the training environment to production in a reliable and scalable way.
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