About the Structuring Machine Learning Projects category

Welcome to the DLS Course 3: Structuring Machine Learning Projects Discourse Page!

In this course, you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader.

By the end, you will be able to diagnose errors in a machine learning system; prioritize strategies for reducing errors; understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance; and apply end-to-end learning, transfer learning, and multi-task learning.

Please feel free to search for a topic that you’re interested in or start one of your own if you don’t find what you are looking for!

This is also a standalone course for learners who have basic machine learning knowledge. This course draws on Andrew Ng’s experience building and shipping many deep learning products. If you aspire to become a technical leader who can set the direction for an AI team, this course provides the “industry experience” that you might otherwise get only after years of ML work experience.