Classic unsupervised

• Implement the k-means clustering algorithm
• Implement the k-means optimization objective
• Initialize the k-means algorithm
• Choose the number of clusters for the k-means algorithm
• Implement an anomaly detection system
• Decide when to use supervised learning vs. anomaly detection
• Implement the centroid update function in k-means
• Implement the function that finds the closest centroids to each point in k-means

Recommender Systems

• Implement collaborative filtering recommender systems in TensorFlow
• Implement deep learning content based filtering using a neural network in TensorFlow
• Understand ethical considerations in building recommender systems

Reinforcement Learning

• Implement the k-means clustering algorithm
• Implement the k-means optimization objective
• Initialize the k-means algorithm
• Choose the number of clusters for the k-means algorithm
• Implement an anomaly detection system
• Decide when to use supervised learning vs. anomaly detection
• Implement the centroid update function in k-means
• Implement the function that finds the closest centroids to each point in k-means