What you’ll learn
- How to choose a machine learning model family
- How to choose the parameters of a best-fitting model within a family
- Comon modeling assumptions and their trade-offs
- No prerequisites, this course is intended for all audiences.
- Any prior modeling activities will enrich your experience.
Welcome to this short course on choosing machine learning models.
One of the toughest questions to answer for beginners and experienced data scientist alike is “Which model should I use?” This course shows some good practices for how to do that, and covers some of the deep issues that you will bump up against in every model selection problem.
It was originally included as part of my polynomial regression course, but this particular block of content I wanted to make sure was freely accessible to everyone.
Who this course is for:
- Intermediate machine learning and data science students
- Anyone curious about the concepts behind machine lerning