What this resource explores
An introduction to machine learning from the perspective of modeling and prediction, including representation, generalization, supervised learning and reinforcement learning.
- Learning problems and representation
- Overfitting and generalization
- Supervised and reinforcement learning
Who it is for
Learners preparing to study predictive models and machine-learning methods.
Background & preparation
Recommended preparation: Python programming, calculus and linear algebra, as listed by MIT Open Learning Library.
A way to approach it
Start by identifying the learning problem, representation and evaluation question. Connect supervised and reinforcement learning to the examples in the source materials.
Edition & context
The OCW listing is Fall 2020 and links to Open Learning Library. Learning materials and any platform conditions belong to MIT, not reflib.