Machine Learning Models

Implementation of classic ML and DL models from scratch: theoretical and practical parts

Classic ML:

• Linear and Logistic Regressions
• KNN and Clustering
• SVM
• Decision Trees
• Random Forest
• Gradient Boosting
• Boosting Class
• Cross-Validation & GridSearch
• Randomized & Bayes Searches
• Bias Variance Tradeoff
• PCA

Deep Learning & NLP:

• Neural Networks
• RNN
• RNN Practice
• Word2Vec
• xLSTM

Learning to Rank & RecSys:

• Ranking
• RecSys