Lecture 5: ML Projects (Full Stack Deep Learning - Spring 2021)
In this video, you will learn how to set up Machine Learning projects like a pro. This includes an understanding of the ML lifecycle, an acute mind of the feasibility and impact, an awareness of the project archetypes, and an obsession with metrics and baselines.
An extensive summary of this lecture can be accessed in this document: https://docs.google.com/document/d/1A...
00:00 - Introduction
01:45 - Why Do ML Projects Fail?
02:53 - Lecture Overview and Running Case Study
06:14 - Lifecycle (Thinking about the activities in an ML project)
12:53 - Prioritizing Projects (Assessing the feasibility and impact of the projects)
36:51 - Archetypes (Knowing the main categories of projects and implications for project management)
49:06 - Metrics (Picking a single number to optimize)
01:02:36 - Baselines (Figuring out if your model is performing well)
01:10:21 - Conclusion