Responsibilities: graduate teaching assistant. The course covers machine learning basis, popular ML models (e.g., Decision Trees, KNN, Naive Bayes, SVM, Ensemble Learning, Clustering, Neural Networks, etc.), use of Python libraries (e.g., Numpy, Keras, Tensorflow).

Check out the links for Numpy and Keras & Tensorflow tutorials.