Grokking-Deep-Learning-with-Julia

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Grokking-Deep-Learning-with-Julia

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# Grokking-Deep-Learning

This repository is a Julia companion to the book "Grokking Deep Learning", [available here](https://manning.com/books/grokking-deep-learning?a_aid=grokkingdl&a_bid=32715258 "Grokking Deep Learning").

You can set up your environment from Julia by running the commands below

julia> cd("Grokking-Deep-Learning-with-Julia/")

#press ']' to enter pkg mode
    (@v1.4) pkg> activate .

(Grokking-Deep-Learning-with-Julia) pkg> instantiate

[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/deepaksuresh/Grokking-Deep-Learning-with-Julia/master)

- [Chapter 3 - Forward Propagation - Intro to Neural Prediction](https://github.com/deepaksuresh/grokJulia/blob/master/Chapter3%20-%20Forward%20Propagation%20-%20Intro%20to%20Neural%20Prediction.ipynb)
- [Chapter 4 - Gradient Descent - Into to Neural Learning](https://github.com/deepaksuresh/grokJulia/blob/master/Chapter4%20-%20Gradient%20Descent%20-%20Intro%20to%20Neural%20Learning.ipynb)
- [Chapter 5 - Generalizing Gradient Descent - Learning Multiple Weights at a Time](https://github.com/deepaksuresh/grokJulia/blob/master/Chapter5%20-%20Generalizing%20Gradient%20Descent%20-%20Learning%20Multiple%20Weights%20at%20a%20Time.ipynb)
- [Chapter 6 - Intro to Backpropagation - Building your first DEEP Neural Network](https://github.com/deepaksuresh/grokJulia/blob/master/Chapter6%20-%20Intro%20to%20Backpropagation%20-%20Building%20Your%20First%20DEEP%20Neural%20Network.ipynb)
- [Chapter 8 - Intro to Regularization - Learning Signal and Ignoring Noise](https://github.com/deepaksuresh/grokJulia/blob/master/Chapter8%20-%20Intro%20to%20Regularization%20-%20Learning%20Signal%20and%20Ignoring%20Noise.ipynb)
- [Chapter 9 - Intro to Activation Functions - Learning to Model Probabilities](https://github.com/deepaksuresh/grokJulia/blob/master/Chapter9%20-%20Intro%20to%20Activation%20Functions%20-%20Modeling%20Probabilities.ipynb)
- [Chapter 10 - Intro to Convolutional Neural Networks - Learning Edges and Corners](https://github.com/deepaksuresh/grokJulia/blob/master/Chapter10%20-%20Intro%20to%20Convolutional%20Neural%20Networks%20-%20Learning%20Edges%20and%20Corners.ipynb)
- [Chapter 11 - Intro to Word Embeddings - Neural Networks which Understand Language](https://github.com/deepaksuresh/grokJulia/blob/master/Chapter11%20-%20Intro%20to%20Word%20Embeddings%20-%20Neural%20Networks%20that%20Understand%20Language.ipynb)
- [Chapter 12 - Intro to Recurrence (RNNs) - Predicting the Next Word](https://github.com/deepaksuresh/grokJulia/blob/master/Chapter12%20-%20Intro%20to%20Recurrence%20-%20Predicting%20the%20Next%20Word.ipynb)
- [Chapter 13 - Intro to Automatic Differentiation](https://github.com/deepaksuresh/grokJulia/blob/master/Chapter13%20-%20Intro%20to%20Automatic%20Differentiation%20-%20Let's%20Build%20A%20Deep%20Learning%20Framework.ipynb)
- [Chapter 14 - Exploding Gradients Example](https://github.com/deepaksuresh/grokJulia/blob/master/Chapter14%20-%20Exploding%20Gradients%20Examples.ipynb)
- [Chapter 14 - Intro to LSTMs](https://github.com/deepaksuresh/grokJulia/blob/master/Chapter14%20-%20Intro%20to%20LSTMs%20-%20Learn%20to%20Write%20Like%20Shakespeare.ipynb)
- [Chapter 14 - Intro to LSTMs - Part 2](https://github.com/deepaksuresh/grokJulia/blob/master/Chapter14%20-%20Intro%20to%20LSTMs%20-%20Part%202%20-%20Learn%20to%20Write%20Like%20Shakespeare.ipynb)
- [Chapter 15 - Intro to Federated Learning](https://github.com/deepaksuresh/grokJulia/blob/master/Chapter15%20-%20Intro%20to%20Federated%20Learning%20-%20Deep%20Learning%20on%20Unseen%20Data.ipynb)

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