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2017spring

Deep Learning (for Computer Vision) Module - Spring 2017

abtextsumm

Abstractive Summarization IJCAI paper code

adv-r

Advanced R programming: a book

anago

Bidirectional LSTM-CRF for Sequence Labeling. Easy-to-use and state-of-the-art performance.

annoy

Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk

artificial-intelligence-deep-learning-machine-learning-tutorials

A comprehensive list of ML tutorials - initially originally created by Donne Martin and will be expanded in areas of AI/Deep Learning / Machine Vision and industry specific areas such as Automotives, Retail, Pharma, Medicine, Healthcare by me.

arxiv-sanity-preserver

Web interface for browsing, search and filtering recent arxiv submissions

autokeras

This is an automated machine learning (AutoML) package.

awesome-2vec

Curated list of 2vec-type embedding models

awesome-awesomeness

A curated list of awesome awesomeness

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

awesome-nlp

:book: A curated list of resources dedicated to Natural Language Processing (NLP)

awesome-rnn

Recurrent Neural Network - A curated list of resources dedicated to RNN

banditlib

Library of contextual bandits algorithms

bigdata-ecosystem

BigData Ecosystem Dataset

bios8366

Advanced Statistical Computing at Vanderbilt University's Department of Biostatistics

blstm-crf-ner

A NER model (B-LSTM + CRF + word embeddings) implemented using Tensorflow

books

bounter

Efficient Counter that uses a limited (bounded) amount of memory regardless of data size.

caffe

Caffe: a fast framework for deep learning. For the most recent version checkout the dev branch. For the latest stable release checkout the master branch.

cltk

The Classical Language Toolkit

cnn-parallel

Parallel Implementation of CNN on all major framework - Keras, Tensorflow etc.

cofactor

CoFactor: Regularizing Matrix Factorization with Item Co-occurrence

comp6781grouppres

Slides for a presentation on "Topic Detection and Tracking"

cornell-coder

coursera-ml

Andrew Ng's Coursera ML coding exercises and notes

courses

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

courses-1

fast.ai Courses

crf

crf-1

CRF is a Java implementation of Conditional Random Fields, an algorithm for learning from labeled sequences of examples. It also includes an implementation of Maximum Entropy learning.