In this first video of my Machine Learning Foundations series, I introduce the basics of Linear Algebra and how Linear Algebra relates to Machine Learning, as well as providing a brief lesson on the origins and applications of modern algebra.
There are eight subjects covered comprehensively in the ML Foundations series and this video is from the first subject, "Intro to Linear Algebra". More detail about the series and all of the associated open-source code is available at github.com/jonkrohn/ML-foundations
The next video in the series is here: youtu.be/ibTYANFwrNc
The playlist for the entire series is here: youtube.com/playlist?list=PLRDl2inPrWQW1QSWhBU0ki-jq_uElkh2a
This course is a distillation of my decade-long experience working as a machine learning and deep learning scientist, including lecturing at New York University and Columbia University, and offering my deep learning curriculum at the New York City Data Science Academy. Information about my other courses and content is at jonkrohn.com
Dr. Jon Krohn is Chief Data Scientist at untapt, and the #1 Bestselling author of Deep Learning Illustrated, an interactive introduction to artificial neural networks. To keep up with the latest from Jon, sign up for his newsletter at jonkrohn.com, follow him on Twitter @JonKrohnLearns, and on LinkedIn at linkedin.com/in/jonkrohn
