Third Assignment in 'Practical topics in Machine Learning' course by Dr. Kfir Bar at Bar-Ilan University.
In the first part, I had to implement a variation of Random Forest, which we will call "weighted" random forest (WRF vs. RF). The WRF model had to support both, classification as well as regression and used DecisionTreeClassifier and DecisionTreeRegressor as the underlying trees.
In the second part, I had to evaluate my implementation, and compare it with RandomForestClassifier and RandomForestRegressor. For classification I used the Fashion MNIST dataset and For regression I used the California housing dataset.
Score: 100