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Data Scientist: Statistics & Machine Learning
Learn the statistics behind the models, then build, tune and evaluate the most important machine learning algorithms with scikit-learn — from linear regression to gradient boosting.
What you'll be able to do Reason about probability, sampling and hypothesis tests Train regression, classification and clustering models Understand how trees, forests and boosting work Build leak-free scikit-learn pipelines Evaluate models with the right metrics and cross-validation Compare algorithms on a real problem Watch each video, run the notebook, then take the quiz at the bottom of the lesson. Tick Mark as complete to track your progress (saved in this browser).
Mathew K Analytics
