Covers: implementation of RMSProp

- How to implement RMSprop in Keras?

In the last module of the RMSprop shortlist, we are going to learn about how to implement RMSprop in Keras by calling tf.keras.optimizers.RMSprop . This is normally how we are going to call RMSprop as an optimizer in different projects

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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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