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Latest commit c51bb44 Dec 9, 2017 Sachinthaka Abeywardana Sachinthaka Abeywardana GANs and Pandas tutoial
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data Moved data to data folder Sep 1, 2017
data_science GANs and Pandas tutoial Dec 8, 2017
images Starting GANs Oct 30, 2017
misc put logo and windows instructions Sep 19, 2017
.gitignore Updated Readme for https and dogo! Sep 15, 2017
CODE_OF_CONDUCT.md license and code of conduct Sep 1, 2017
Cheat Sheet.md cheat sheet Sep 1, 2017
Contributing.md license and code of conduct Sep 1, 2017
Dockerfile Changed Dockerfile Jun 19, 2017
Dockerfile.backup Stateful LSTMs Aug 22, 2017
LICENSE license and code of conduct Sep 1, 2017
Lesson 0 - LinRegression.ipynb Included References Oct 8, 2017
Lesson 01 - PenalisedRegression - Solutions.ipynb Changed some folder locations Sep 15, 2017
Lesson 01 - PenalisedRegression.ipynb Changed some folder locations Sep 15, 2017
Lesson 02 - GradientDescent.ipynb Half way through Transfer Learning lesson Jul 24, 2017
Lesson 03 - TF_intro.ipynb Changed some folder locations Sep 15, 2017
Lesson 04 - NeuralNets.ipynb Half way through Transfer Learning lesson Jul 24, 2017
Lesson 04 - Part 2 - Keras Neural Nets.ipynb Redid lesson 1 Sep 3, 2017
Lesson 05 - Keras Sentiment Analysis - Solutions.ipynb Redid original lesson 5 - sentiment analysis Sep 13, 2017
Lesson 05 - Keras Sentiment Analysis.ipynb Redid original lesson 5 - sentiment analysis Sep 13, 2017
Lesson 06 - contraception.ipynb Changed some folder locations Sep 15, 2017
Lesson 07 - Word2vec.ipynb Changed some folder locations Sep 15, 2017
Lesson 08 - Bike Sharing - Solutions.ipynb Added Fake News Classifier Sep 12, 2017
Lesson 08 - Bike Sharing.ipynb Added Fake News Classifier Sep 12, 2017
Lesson 09 - Hyperparameters - Solutions.ipynb Half way through Transfer Learning lesson Jul 24, 2017
Lesson 09 - Hyperparameters.ipynb Half way through Transfer Learning lesson Jul 24, 2017
Lesson 10 - XGBoost + Scikit learn - Solutions.ipynb Changed some folder locations Sep 15, 2017
Lesson 10 - XGBoost + Scikit learn.ipynb Changed some folder locations Sep 15, 2017
Lesson 11 - Convolutional Neural Nets - Solutions.ipynb Changed some folder locations Sep 15, 2017
Lesson 11 - Convolutional Neural Nets.ipynb Changed some folder locations Sep 15, 2017
Lesson 12 - CIFAR10 CNN - Solutions.ipynb Half way through Transfer Learning lesson Jul 24, 2017
Lesson 12 - CIFAR10 CNN.ipynb Modified Readme for DeepSchool.io Jul 1, 2017
Lesson 13 - Transfer Learning - Solutions.ipynb Changed some folder locations Sep 15, 2017
Lesson 13 - Transfer Learning.ipynb Stateful LSTMs Aug 22, 2017
Lesson 14 - Sentiment Analysis - RNNs - Solutions.ipynb Made exercise lesson for Lesson 19 Oct 9, 2017
Lesson 14 - Sentiment Analysis - RNNs.ipynb Redid lesson 1 Sep 3, 2017
Lesson 15 - LSTM Shakespeare generator - Solutions.ipynb Included References Oct 8, 2017
Lesson 15 - LSTM Shakespeare generator.ipynb Lesson 13 Sentiment Analysis Aug 29, 2017
Lesson 16 - LSTM Trump Tweets - Solutions.ipynb finalised Trump LSTMs Sep 2, 2017
Lesson 16 - LSTM Trump Tweets.ipynb finalised Trump LSTMs Sep 2, 2017
Lesson 17 - LSTM part 2 Trump Tweets - Solutions.ipynb Lesson 13 Sentiment Analysis Aug 29, 2017
Lesson 17 - LSTM part 2 Trump Tweets.ipynb Lesson 13 Sentiment Analysis Aug 29, 2017
Lesson 18 - Fake News Classification - Solutions.ipynb Modified fake news lesson Sep 19, 2017
Lesson 18 - Fake News Classification.ipynb Added Fake News Classifier Sep 12, 2017
Lesson 19 - Seq2Seq - Date translator - Solutions.ipynb Finalised seq2seq lesson with video Sep 30, 2017
Lesson 19 - Seq2Seq - Date translator.ipynb Made exercise lesson for Lesson 19 Oct 9, 2017
Lesson 20 - Deep Q Learning - Solutions.ipynb Starting GANs Oct 30, 2017
Lesson 20 - Deep Q Learning.ipynb Starting GANs Oct 30, 2017
Lesson 21 - Generative Adversarial Networks.ipynb GANs and Pandas tutoial Dec 8, 2017
Lesson 22 - Final Thoughts.ipynb Added final thoughts Nov 13, 2017
README.md Removed Docker compose in favour of a run.sh file Dec 2, 2017
docker-compose.yml Stateful LSTMs Aug 22, 2017
run.sh Removed Docker compose in favour of a run.sh file Dec 2, 2017
utilities.py half way with translation Sep 26, 2017

README.md

DeepSchool.io

logo

License

Goals

  1. Make Deep Learning easier (minimal code).
  2. Minimise required mathematics.
  3. Make it practical (runs on laptops).
  4. Open Source Deep Learning Learning.

Installation

  1. Install Docker https://www.docker.com/
  2. Use the following commands to run from docker1.
git clone https://github.com/sachinruk/deepschool.io.git
cd deepschool.io
bash run.sh
  1. Now go to localhost:9000 on your browser to start using the jupyter notebooks.
  2. (Optional) If you are on a mac/windows some of the examples may not work because the docker image may run out of memory. Hence under preferences in docker there is the option to increase the allocated memory. I have set it to 8GB. Run docker-compose up again if you reset memory.

See here for installing on windows.

Contents

  1. Lesson 0: Introduction to regression.
  2. Lesson 1: Penalising weights to fit better (scikit learn intro)

Mathematics (optional)

  1. Lesson 2: Gradient Descent. Using basic optimisation methods.
  2. Lesson 3: Tensorflow intro: zero layer hidden networks (i.e. normal regression).
  3. Lesson 4: Tensorflow hidden layer introduction.

Deep Learning

  1. Lesson 5: Using Keras to simplify multi layer neural nets.
  2. Lesson 6: Embeddings to deal with categorical data. (Keras)
  3. Lesson 7: Word2Vec. Embeddings to visualise words. (Tensorflow)
  4. Lesson 8: Application - Bike Sharing predictions
  5. Lesson 9: Choosing Number of Layers and more
  6. Lesson 10: XGBoost - A quick detour from Deep Learning
  7. Lesson 11: Convolutional Neural Nets (MNIST dataset)
  8. Lesson 12: CNNs and BatchNormalisation (CIFAR10 dataset)
  9. Lesson 13: Transfer Learning (Dogs vs Cats dataset)

Advanced Topics

  1. Lesson 14: LSTMs - Sentiment analysis.
  2. Lesson 15: LSTMs - Shakespeare.
  3. Lesson 16: LSTMs - Trump Tweets.
  4. Lesson 17: Trump - Stacking and Stateful LSTMs.
  5. Lesson 18: Fake News Classifier

Support

You can ask questions and join the development discussion:

Support Us

There's a few ways you can support this initiative:

  1. Right now this is very much a self funded project. If you wish to see more and more high quality tutorials and videos support us at: https://www.patreon.com/deepschoolio
  2. Subscribe to our YouTube channel here.
  3. Star this repository and share it!

Meetup

First meetup node: https://www.meetup.com/DeepSchool-io/

YouTube playlist

Find the corresponding video tutorial here (not all notebooks have an associated video) https://www.youtube.com/playlist?list=PLIx9QCwIhuRS1SPS9LHF7VjvZyM1g2Swz

Notes

1: Refer to this Dockerfile and this for information on how the docker image was built.