🥋 tf-kata 🥋

Repository that is losely inspired by CS 20SI: Tensorflow for Deep Learning Research

Models

Linear regression

• linear regression using normal equation
• linear regression with SGD
• linear regression with polynomial kernel: linear regression with polynomial kernel aka polynomial regression.
• linear regression with OOP: simple example how to organize code with classes.

Logistic regression

• logistic regression trained on obligatory MNIST.

Autoencoders

• Simple 2-layer autoencoder without weight-tying trained on obligatory MNIST.
• Variational Auto-Encoder using tf.contrib.distributionss trained on obligatory MNIST.

CNN

• Classification with CNN on MNIST using Dataset, Estimator and Experiment API

Layers

• highway layer 'Highway Networks' paper

NLP Embeddings

• charcter-level CNN word embeddings from Character Aware Language Models

Infrastructure and Debugging

Tensorboard

• minimal example
• logistic regression with train and validation split: validation and training error plotted on the same graph.
• ops benchmarking with tensorboard and Timeline object

Pipelines

• custom datastructures: MNIST as a custom dataset

Model managament

• training and saving: Train simple linear reggresion and save it.
• loading saved model: Load placeholder and ouput tensor and use it for prediction.
• training and saving in Keras: Train simple linear reggresion in Keras and save it.
• loading saved model in Keras: Load model and use it in production.
• exporting a clean graph: Select sub-graph relevant to operations, freeze weights and export definition
• loading and serving a frozen graph: Load the graph and serve it using Falcon API endpoint