Catalogue · Faculty of Machine Learning
ML 201
Machine Learning Specialization
Andrew Ng’s modern rewrite of the course that introduced a generation to machine learning. Supervised learning from linear regression through neural networks and tree ensembles, plus unsupervised methods and recommenders, in Python with NumPy and scikit-learn. Gentle in mathematics, honest in substance — the front door of this faculty.
Syllabus
- supervised learning
- regression and classification
- neural networks
- decision trees
- recommender systems
Held at DeepLearning.AI & Stanford Online. The materials remain theirs; the structure is ours. Finished it? Record it in your transcript.