This course is organized around algorithmic issues that arise in machine learning. Modern machine learning systems are often built on top of algorithms that do not have provable guarantees, and it is the subject of debate when and why they work. In this c...

Mix-and-match approaches for visualizing data and interpreting machine learning models and results. (more…)

Mastering BigData and Machine Learning with Apache Spark 2.0...

The last two decades have yielded us some great understandings about Software Development. A big part of that is due to the emergence of DevOps and it’s wide adoption throughout the industry. (more…)

This blog post is my attempt to give an overview of the sub-field of machine learning interpretability. I do not intend for this post to be necessarily comprehensive, but my goal is to review conceptual frameworks, existing research, and future directions... (more…)