This is repo that contains some notebooks related to ML methods and data analytics

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(1) ML Methods that have been implemented from scratch: K-Means, PCA, IsolatedForrest, Gradient Boosting

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(2) Anomaly detection methods:

Unsupervised: PCA, tSNE, UMAP, GMM, DBSCAN, Mahabolis, Isolted Forrest, LOF, OneClass SVM

Unbalanced Dataset: SMOTE, XGBOOST, and random forest with class weight, EasyEnsembleClassifier, BalancedRandomForestClassifier

Deep Learning Methods: Fully connected Network with class weight, AutoEncoder

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(3) Playing with Pandas to manipulate data, we would go nuts here and try everything. tasks are mainly based on Leetcode Pandas tasks