dbernardoj Goto Github PK

aqgridview

A grid view for iPhone/iPad, designed to look similar to NSCollectionView.

bctpy

brain connectivity toolbox for python

biaxial-rnn-music-composition

A recurrent neural network designed to generate classical music.

biosig

crbm-drum-patterns

Python code to do Conditional Restricted Boltzmann machine training applied to drum pattern generation.

deepautocontroller

Build a deep autoencoder. Acoustically monitor the influence of the middle code layer using a Kork nanoKontroller2.

exconly

first kaggle connectome contest

friday-flair-python-reddit-api

homebrew-science

Scientific formulae for the Homebrew package manager

kaggle-ndsb

Winning solution for the National Data Science Bowl competition on Kaggle (plankton classification)

kaggle-seizure-prediction

solution for the American Epilepsy Society Seizure Prediction Challenge

kaggle_eeg

keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano or TensorFlow.

keras_tfrecord

Extending Keras to support tfrecord dataset

lsh

Locality-Sensitive Hashing for Minhash Signatures

lshash

A fast Python implementation of locality sensitive hashing.

lshhdc

LSH based high dimensional clustering for sets and points

matlab-scripts

My MATLAB scripts.

matlab_xltek_epworks_parser

Parses XLTEK epworks files in Matlab

mcts

Python Implementations of Monte Carlo Tree Search

min-loss-hashing

locality sensitive hashing

music_rnn

Music Language Modeling with Recurrent Neural Networks

neo

Collaboration on kaggle contest.

optimal-lsh

This package provides an efficient implementation of locality-sensitve hashing (LSH)

papers

Code for scientific papers of www.ladisk.si

pylearn2

A Machine Learning library based on Theano

python-mingus

Mingus is a music package for Python

python-music-gen

Automatically exported from code.google.com/p/python-music-gen

reddit-hacks

rocalphago

An independent, student-led replication of DeepMind's 2016 Nature publication, "Mastering the game of Go with deep neural networks and tree search" (Nature 529, 484-489, 28 Jan 2016), details of which can be found on their website https://deepmind.com/publications.html.