Basic algorithms of classical machine learning.
Contains:
pandas_basics.ipynb- basic techniques for dealing with dataframes;eda.ipynb- data preprocessing;knn_linreg.ipynb- knn-classifier realization + training sklearn linear model for diamonds price prediction;gd.ipynb- gradient descent realization (+stochastic one) + linear regression realization with l1 and l2 regularization + different losses;texts_classifier.ipynb- sklearn logistic regression for classification tweets by sentiment;trees_rainforest.ipynb- decision tree realization + different types of classifiers from sklearn;boostings_clusters.ipynb- LightGBM, CAtBoost, XGBoost, Kmeans.