Covers: implementation of Gradient Descent

- How to implement Gradient Descent in Python?

In this last module of prerequisite concepts of RMSprop, this code is going to help us understand better how GD works in the python language.

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Contributors

- Objectives
- Learning about RMSprop concept, math behind it and code it in python
- Potential Use Cases
- RMSprop is a gradient based optimization technique used in training neural networks
- Who is This For ?
- INTERMEDIATE

Click on each of the following **annotated items** to see details.

ARTICLE 1. Intro to mathematical optimization

- What is mathematical optimization?
- Why do we need to optimize a cost function in ML algorithms?

10 minutes

VIDEO 2. Gradient Descent

- What is Gradient Decent(GD)?
- How does GD work in python?

10 minutes

LIBRARY 3. Gradient Descent in Python

- How to implement Gradient Descent in Python?

20 minutes

VIDEO 4. RMSprop

- What is RMSprop?
- How does this algorithm work?

8 minutes

ARTICLE 5. RMSprop: Divide the gradient by a running average of its recent magnitude

- Why rprop does not work with mini-batches
- Further developments of rmsprop

10 minutes

LIBRARY 6. RMSprop from scratch in Python

- how to code RMSprop in python from scratch?

10 minutes

LIBRARY 7. Implement RMSprop in Keras

- How to implement RMSprop in Keras?

20 minutes

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