If you didn't find a file for any of the below topics please feel free to email me, so I will upload the same. email: datascience.scout@gmail.com
SUPERVISED LEARNING:
REGRESSION: Linear - Polynomial - Ridge/Lasso CLASSIFICATION: K-NN - Naïve Bayes - Decision Tree - Logistic Regression - Confusion Matrix - SVM TIME SERIES ANALYSIS: Linear & Logistic Regr. - Autoregressive Model - ARIMA - Naïve - Smoothing Technique
UNSUPERVISED LEARNING:
CLUSTERING: K-Means - Agglomerative - Mean-Shift - Fuzzy C-Mean - DBSCAN - Hierarchical - Canopy PATTERN SEARCH: Apriori - FP-Growth - Euclat DIMENSION REDUCTION: PCA - LSA - SVD - LDA - t-SNE RECOMMENDATION ENGINE: Association Rules - Market Basket Analysis - Apriori Algorithm - Real Rating Matrix - IBCF - (Item) - User-Based Collaborative Filtering UBCF - Method & Model
ENSEMBLE METHODS: BOOSTING: AdaBoost - XG Boost - LightGBM - CatBoost. BAGGING: Random Forest STACKING