Google’s fast-paced, practical introduction to machine learning
This course includes:
- 30+ exercises
- 25 lessons
- 15 hours
- Lectures from Google researchers
- Real-world case studies
- Interactive visualizations of algorithms in action
Machine Learning Crash Course does not presume or require any prior knowledge in machine learning. However, to understand the concepts presented and complete the exercises, we recommend that students meet the following prerequisites:
- You must be comfortable with variables, linear equations, graphs of functions, histograms, and statistical means.
- You should be a good programmer. Ideally, you should have some experience programming in Python because the programming exercises are in Python. However, experienced programmers without Python experience can usually complete the programming exercises anyway.
The following sections provide links to additional background material that is helpful.
Machine Learning Crash Course (MLCC) teaches the basics of machine learning through a series of lessons that include:
- video lectures from researchers at Google
- text written specifically for newcomers to ML
- interactive visualizations of algorithms in action
- real-world case studies
While learning new concepts, you’ll immediately put them into practice with coding exercises that walk you through implementing models in TensorFlow: an open-source machine intelligence library.