Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0.
Learn to train and assess models performing common machine learning tasks such as classification, regression and clustering.
Learn how to build and tune predictive models and evaluate how well they will perform on unseen data.
This course teaches the big ideas in machine learning like how to build and evaluate predictive models.
Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.
This course provides a basic introduction to clustering and dimensionality reduction in R from a machine learning perspective.