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This list will help you understand gradient descent for optimization of functions
Potential Use Cases
Mathematical foundations behind Gradient descent
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1. Need for optimization in Deep Learning
It explains why Deep learning algorithms use optimization.
2. Gradient Descent Explained
Provides intuitive understanding of gradient descent as first order optimization algorithm
3. Multivariate calculus
It provides intuitive understanding of multivariate calculus
Application of multivariable calculus to optimization problem
5. Jacobian matrix
Explains what Jacobian captures for multivariable functions.
6. Second derivative as indication of curvature
Explains how to understand the impact of curvature on performance of gradient descent