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advice

A repository of links with advice related to grad school applications, research, phd etc

ai-audio-startups

Community list of startups working with AI in audio and music technology

applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

awesome-cbir-papers

📝Awesome and classical image retrieval papers

awesome-competitive-programming

:gem: A curated list of awesome Competitive Programming, Algorithm and Data Structure resources

awesome-deep-learning-music

List of articles related to deep learning applied to music

awesome-normalizing-flows

Awesome resources on normalizing flows.

awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

capsulenetwork

clmr

Official PyTorch implementation of Contrastive Learning of Musical Representations

clustering_seminar

Algorithms for KMeans, Hierarchichal clustering, EM and DBSCAN

cs231n_cnns

Programming assignments on Deep Learning.

deep_audio_features

Pytorch implementation of deep audio embedding calculation

deephash

An Open-Source Package for Deep Learning to Hash (DeepHash)

dejavu

Audio fingerprinting and recognition in Python

factoranalysismodel

fall2018-tutorials

Tutorials for Fall 2018

git_gym

google-research

Google Research

introduction_to_normalizing_flows

Jupyter Notebook corresponding to 'Going with the Flow: An Introduction to Normalizing Flows'

models

Models and examples built with TensorFlow

neural-audio-fp

normalizing-flows

PyTorch implementation of normalizing flow models

numerical_analysis

Programming assignments on numerical analysis

patternrecognition_seminar

Algorithms for PCA, LDA, Bayes classifier

perlcourse_assignments

plotneuralnet

Latex code for making neural networks diagrams

programmingassignment2

Repository for Programming Assignment 2 for R Programming on Coursera

python-cheatsheet

Comprehensive Python Cheatsheet

pytorch-simclr

A PyTorch reproduction of 'A Simple Framework for Contrastive Learning of Visual Representations' by Ting Chen, et al.