To run examples using code from src you'll need to run python setup.py develop.

Some examples also require graphviz installed (on Ubuntu you can do apt-get install graphviz)

For loading data for word embeddings or coil20 dataset see Makefile.

• Kernel SVMs: fitting sine function, nonlinear classification with RBF kernel

• Transforming nonlinear data with Kernel PCA

• (counterexample) if a dataset is linearly separable then it is linearly separable after applying PCA

• Extractive Summarization in Python, includes one word-embedding based method.

• Nonnegative Matrix Factorization (NMF) for topic modeling - very simple exaple on 20 Newsgroups

• Symmetric Deep Dream - added rotation/mirroring invariance to original Deep Dream code

• Variational Autoencoder (VAE) in Keras - Example of running generative model on very small dataset (Olivetti faces dataset - 400 examples). Adapted and refactored code from Keras project.

• Logistic regression - using Theano (code)

• Basic MXNet - logistic regression & MLP

• GANs in Gluon and in PyTorch on Colab! Using Gluon's Hybrid Blocks which utilize dynamic graphs by default, but can be compiled to static ones

• Visualizing Convolutional Neural Networks in Keras with Quiver

• Minimal CoreNLP Scala notebook