Big Data and Machine Learning Analytics

• Lead weekly coding session to teach 50+ masters students R
• Explain machine learning techniques to students without statistics or computer science backgrounds
• Create curriculum and advise on how to adopt machine learning skills to domain specific applications

Topics include: Linear regression, KNN, LDA, QDA, LASSO, Ridge, PCR, PLS, SVMs, Splines, GAMs, Decision Trees, Random Forest and Boosting, Reinforcement Learning, Neural Networks, and Hierarchical and K-means Clustering