Machine Learning personal cheatsheet

• Pandas and Numpy
• Data Visualization: Matplotlib and Seaborn
• Data Types: discretizations, encodings
• Preprocessing: scaling, standardizations
• Dimensionality Reduction: PCA, LDA
• Supervised Learning: classification, regression, metrics, data leakage
• Linear Regression, Logistic Regression
• Decision Trees: Bagging, Boosting
• Bayesian Learning, QDA
• KNN, SVM
• Anomaly Detection
• Clustering: K-Means, Gaussian Mixture, DBSCAN, Divisive Clustering
• Neural Networks: FF, Deep, optimizers, regularizations, batching
• Recurrent NN, LSTM, Attention, Transformers

Feel free to propose corrections, especially on the mathematical parts!