Introduction

This package is part of the Kadenze Academy program Creative Applications of Deep Learning w/ TensorFlow.

COURSE 1: Creative Applications of Deep Learning with TensorFlow I (Free to Audit)
Session 1: Introduction to TensorFlow
Session 2: Training A Network W/ TensorFlow
Session 3: Unsupervised And Supervised Learning
Session 4: Visualizing And Hallucinating Representations
Session 5: Generative Models

COURSE 2: Creative Applications of Deep Learning with TensorFlow II (Program exclusive)
Session 1: Cloud Computing, GPUs, Deploying
Session 2: Mixture Density Networks
Session 3: Modeling Attention with RNNs, DRAW
Session 4: Image-to-Image Translation with GANs

COURSE 3: Creative Applications of Deep Learning with TensorFlow III (Program exclusive)
Session 1: Modeling Music and Art: Google Brain’s Magenta Lab
Session 2: Modeling Language: Natural Language Processing
Session 3: Autoregressive Image Modeling w/ PixelCNN
Session 4: Modeling Audio w/ Wavenet and NSynth

This is a flask application which serves a pre-trained TensorFlow model.

Instructions

First build the docker image:

docker build -t flask-app .

Then run the docker image, mapping the UWSGI server on port 80 to any local port you choose, e.g. 5000:

docker run -p 5000:80 -it flask-app

You should then be able to use curl to test the server:

curl localhost:5000