Today marks the beginning of a new thematic segment of videos in my ML Foundations series. This segment builds on the Limits content already covered to clearly illustrate how Differentiation works and how we find Derivatives.
Through a combination of color-coded equations, paper-and-pencil exercises, and hands-on Python code demos, the videos in this segment instill a deep understanding of how differentiation allows us to find derivatives.
More specifically, the videos cover:
• The Delta Method
• The Differentiation Equation
• Differentiation Notation
• Rules that enable us to quickly calculate the derivatives of a wide range of functions, including those found throughout machine learning
New videos are published every Monday and Thursday. The playlist for my Calculus for ML course is here.
More detail about my broader ML Foundations series and all of the associated open-source code is available in GitHub here.
