Covers: theory of Jacobian matrix

Explains what Jacobian captures for multivariable functions.

Read till Jacobian determinant section

Wikipedia

Hardik Sahi**Total time needed: **~4 hours

- Learning Objectives
- This list will help you understand gradient descent for optimization of functions
- Potential Use Cases
- Mathematical foundations behind Gradient descent
- Target Audience
- INTERMEDIATE

Go through the following **annotated items** *in order*:

ARTICLE 1. Need for optimization in Deep Learning

It explains why Deep learning algorithms use optimization.5 minutes

ARTICLE 2. Gradient Descent Explained

Provides intuitive understanding of gradient descent as first order optimization algorithm20 minutes

VIDEO 3. Multivariate calculus

It provides intuitive understanding of multivariate calculus60 minutes

VIDEO 4. Optimization

Application of multivariable calculus to optimization problem 60 minutes

ARTICLE 5. Jacobian matrix

Explains what Jacobian captures for multivariable functions.20 minutes

BOOK_CHAPTER 6. Second derivative as indication of curvature

Explains how to understand the impact of curvature on performance of gradient descent30 minutes

Previewing stream ** Math and Foundations**

Upcoming Live Sessions

Videos

Learning Packages

Past Capstones

People

Search for a tag: