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A list of resources used in Applied Data Science

aicollaboratory

Collaboratory for the evaluation, comparison and classification of (A)I

ann_notebooks

Tutorial of different Artificial Neural Networks using the platform IPython Notebook (http://ipython.org/notebook.html)

avr4dtetris

background_check

betacal

bios366

Advanced Statistical Computing at Vanderbilt University's Department of Biostatistics

bluecrystal4_demo

This is a set of demos to illustrate how to use Blue Crystal Phase 4 at University of Bristol.

caffe

Caffe: a fast open framework for deep learning.

calibration_tutorial

Tutorial and material for a workshop about the calibration of classification models.

catinabox

Intro to Testing and Test Automation in Python

classification_with_reject

Material to generate figures and ideas related to multiclass classification with reject option

cnn_visualization_caffe

Some example networks to visualize their activations and gradients using the Caffe framework and Ipython Jupyter

connectivity-fund

contiki

The official git repository for Contiki, the open source OS for the Internet of Things

d3-chord-diagrams

Example Chord Diagrams in D3

datapythonista.github.io

datasets

Datasets and experiments that I develop in each of them.

deep_calibration

Experiments to test the performance of calibration techniques on Artificial Neural Networks

deeplearningimplementations

Implementation of recent Deep Learning papers

deeptrip

Code based on Google Deepdream to visualize all the hidden layers.

diary

Script to create diary annotations and explore, visualize and mantain copies of it.

diarypy

Python class to save the partial results of a running experiment in a set of notebooks (csv files) and images.

dirichlet_python

dotfiles

My Linux dotfiles

edward

A library for probabilistic modeling, inference, and criticism. Deep generative models, variational inference. Runs on TensorFlow.

enrsr.github.io

Research homepage

entity_extractor