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1. Machine-Learning-Classification-Models Machine-Learning-Classification-Models Public

   Classification Models: GNB, LDA, QDA, LogReg, Decision Tree, Random Forest, Bagging, AdaBoost, GraBoost, XGBoost, Stacking for SAheart dataset

   Jupyter Notebook

2. Clustering-methods-for-customer-segmentation Clustering-methods-for-customer-segmentation Public

   Customer Segmentation (Dimension reduction PCA, Kmeans, Hierarchical clustering, DBSCAN, Spectral clustering, Gaussian Mixture Model ) for Credit Card Users Dataset

   Jupyter Notebook

3. ML-for-cryptocurrencies-trading ML-for-cryptocurrencies-trading Public

   ML (LogReg, KNN, XGB, Random Forest) and DL (LSTM) for Bitcoin Trading with Transfer Learning on Other Cryptocurrencies

   Jupyter Notebook

4. Deep-learning Deep-learning Public

   Intro to DL by MIT 6S191 course and DL course in Master Quantitative Finance program

   Jupyter Notebook

5. SSVI-calibration SSVI-calibration Public

   SSVI calibration under Static arbitrage constraints and numerical application to SPX options

   R

6. Credit-risk-modeling-IRB-PD-EAD-LGD Credit-risk-modeling-IRB-PD-EAD-LGD Public

   Jupyter Notebook