Zero to One — A Ton of Awe-Inspiring Deep Learning Demos with Code for Beginners

Check it out!

#13 — Artistic Style Transfer with Videos

Someone here —

Deep Learning in Production

— said they wanted deep learning examples that they can just download and run. No Math. No Theory. No Books.

Zero to One — A Ton of Awe-Inspiring Deep Learning Demos with Code for Beginners

It’s difficult to find deep learning examples that are open source and that also run first try without stepping through dependency hell, so try this:

Below are 10 models I have downloaded and started running on my MacBook Pro or AWS in under 10 minutes. All ran several days to several months ago — just download and go. They finish in between 5s (pre-trained neural networks) and several hours (GPU-intensive neural network training) time. But you’ve got 5 seconds, right?

Email me if the following doesn’t work for you. Seriously!

Email — Sam@EnterpriseDeepLearning.com

The list is split into two parts —

Part 1: Deep Learning on AWS & Using APIs

Part 2: Deep Learning on iOS.

Here you go!

Part 1: Deep Learning on AWS & Using APIs

1 — Gated Conditional Pixel Convolutional Neural Network using TensorFlow

Model:

anantzoid/Conditional-PixelCNN-decoder

Demo:

Deep Learning: Zero to One - “Image Generation” Essay

Paper:

[1606.05328] Conditional Image Generation with PixelCNN Decoders

2— Value Iteration Networks using TensorFlow — Best Paper Award NIPS ‘16

Model:

TheAbhiKumar/tensorflow-value-iteration-networks

Demo:

3 — Flappy Bird using Deep Reinforcement Learning (Deep Q-learning)

Model:

yenchenlin/DeepLearningFlappyBird

Demo (Amazon version):

4 — LSTM Music Generation with Google Magenta Basic RNN

Model:

tensorflow/magenta

Demo:

5 — Live Captioning using Speech APIs on iOS

Model:

zats/SpeechRecognition

Demo:

6 — Spotify Artist Search using Speech APIs on iOS

Model:

marcdown/SayWhat

Demo:

7 — Symbolic AI Speech Recognition with iOS 10 Speech APIs

Model:

darjeelingsteve/speech-recognition

Demo:

Article: https://medium.com/@darjeelingsteve/controlling-your-app-using-speech-f25aacbd9e1a

8— Video Style Transfer using Torch 7

Model:

manuelruder/artistic-videos

Demo:

Setting up on an EC2 GPU Step-by-step (start at p.17):

9 — Algorithmia API Photo Colorizer

Model:

Colorize Black and White Photos

Demo:

10— Clarifai Information Retrieval for Videos on Android

Model:

hanuor/onyx

Demo:

LinkedIn

Part 2: Deep Learning On iOS

1 — Convolutional Neural Network using TensorFlow on iOS

Model:

LunarFlash/convolutional-neural-network-image-recognition

Demo:

2 — MNIST (of course) on iOS

Model:

hollance/Forge/tree/master/Examples/MNIST

Demo:

(took a minute to get Sketch right)

3 — MobileNets on iOS

Model:

hollance/Forge/tree/masters/Examples/MobileNets

Demo:

4 — YOLO on iOS (**This is helping the blind ‘see’ for the first time! **)

Model:

hollance/Forge/tree/master/Examples/YOLO

Demo:

5 — Inception on iOS

Model:

hollance/Forge/tree/master/Examples/Inception

Demo:

In the theme of learning by doing — I highly recommend Josh Gordon’s Google Developers Deep Learning videos too:

Thank you to the model creators: Algorithmia, Clarifai, Anant Gupta, Abhishek Kumar, Yen-Chen Lin, Sash Zats, Marc Brown, Terry Wang, Matthijs Hollemans, Stephen Anthony, Manuel Ruder, and Shantanu Johri.

Github List:

samdeeplearning/deep-learning-download-and-run

— Sam