andhus/stockholm-ai-reading-group

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andhus/stockholm-ai-reading-group

andhus

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Temporary place for code/notebooks/slides from Stockholm-AI reading group.

dirhash-python

Python module and CLI for hashing of file system directories based on the Dirhash Standard.

dirhash

The Dirhash Standard: A formal procedure for hashing of a filesystem directory.

extkeras

Playground for implementing custom layers and other components compatible with keras, with the purpose to learn the framework better and perhaps in future offer some utils for others.

scantree

Flexible recursive directory iterator: `scandir` meets `glob("**", recursive=True)`

DLMeetupSept2015

Tutorial on how to get started with Recurrent Neural Networks using Blocks and Fuel.

Jupyter Notebook

adversarial-autoencoder

Theano/Blocks implementation of the paper "Adversarial Autoencoders" by Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian Goodfellow (http://arxiv.org/abs/1511.05644)

Jupyter Notebook

stardag

Declarative Composable DAGs

time-series-h5py

Abstraction layer on top of h5py for storing time-indexed Pandas data (Series, DataFrame). Focus is fast retrieval of range and index queries but should also support flexible modification of data.

url-generation

RNN generation of phishy/non-phisy URL:s.

deep-dynamic-graphs

Some tutorials put together for talk at StockholmAI Study Group 2017-06-01: "Application of RNNs to Multiple Asynchronous Event-Driven Data Streams"

Jupyter Notebook