Machine Learning Specialization

By the end of this Specialization, you will be ready to:

• Build machine learning models in Python using popular machine learning libraries NumPy and scikit-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.