The course is based on Geron's "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems".
This repository contains the individual work done in the course (although each workshop starts in an in-person class so we get to discuss and share details with other students and profs). There's one workshop ("taller" in spanish) per week, contained in each tN folder (the t stands for "taller").
- Titanic survivor binary classifier, based on features of every passenger. Concluded that the most significant features are the passenger's class and sex (as women were prioritized in the lifeboats).
- IMDB movie reviews sentiment binary classifier. Final result of 87% accuracy in test set (we weren't taking into account precision, recall, F1 and other metrics yet), using stop words, bigrams and tf-idf metric for weighting.
- Bike rental regressor. Cross validation RMSLE of ~0.37 (the error would probable be a lot higher on the test set) using random forest with gradient boosting (XGBoost), Kaggle top 5 leaderboard error is in the 0.35 ball park.