MACHINE LEARNING

"Build machine learning models in Python using popular machine learning libraries NumPy & sci-kit-learn
Build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression."
"Build and train a neural network with TensorFlow to perform multi-class classification
Apply best practices for machine learning development so that your models generalize to data and tasks in the real world
Build and use decision trees and tree ensemble methods, including random forests and boosted trees"
"Use unsupervised learning techniques for unsupervised learning: including clustering and anomaly detection
Build recommender systems with a collaborative filtering approach and a content-based deep-learning method
Build a deep reinforcement learning model"