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3-hour tutorial on building deep learning models with Keras.

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# Keras Tutorial

This repo contains curriculum to support a three-hour introductory workshop on building deep learning models with Keras and TensorFlow. For more samples, an engineering blog, and extended discussion, I sincerely recommend checking out the [Keras website](https://keras.io/), as well as Francois Chollet's phenomenal book, [_Deep Learning with Python_](https://www.manning.com/books/deep-learning-with-python).

### _HOUR 1:_ INTRODUCTION TO DEEP LEARNING
* What is _deep learning_, and why should you care?
* What is _TensorFlow_, and why can it be a pain to use?
* What is _Keras_, and why is it delightful?

### _HOUR 2:_ GETTING STARTED WITH FEEDFORWARD NEURAL NETWORKS
* Building a feedforward neural network by hand, and with `numpy`
* Incorporating back propagation by hand and with `numpy`
* Interpolating values for hidden nodes and building intuition

### _HOUR 3:_ GETTING STARTED WITH KERAS
* Specifying the model (`Sequential()`, `.add()`-ing layers)
* Compiling the model (`.compile()`, adding optimizers, understanding `loss`)
* Fitting the model (`.fit()` with predictors and targets)
* Optimizing the model (changing architectures - nodes, layers)

For questions about coursework, models, data and implementation, please contact [Paige Bailey](mailto:paige.bailey@microsoft.com).

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