Covers: theory of Multivariate calculus
Estimated time needed to finish: 60 minutes
Why this is worth your time
It provides intuitive understanding of multivariate calculus
How to use this item?

Go through sections 'Thinking about multivariate calculus' and 'Derivative of multivariate functions' except Divergence, Curl, Laplacian

Author(s) / creator(s) / reference(s)
Khan Academy
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Gradient Descent

Total time needed: ~4 hours
This list will help you understand gradient descent for optimization of functions
Potential Use Cases
Mathematical foundations behind Gradient descent
Who is this for ?
Click on each of the following annotated items to see details.
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 algorithm
20 minutes
VIDEO 3. Multivariate calculus
It provides intuitive understanding of multivariate calculus
60 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 descent
30 minutes

Concepts Covered

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