ken-may's Stars
sbrugman/deep-learning-papers
Papers about deep learning ordered by task, date. Current state-of-the-art papers are labelled.
endymecy/awesome-deeplearning-resources
Deep Learning and deep reinforcement learning research papers and some codes
src-d/awesome-machine-learning-on-source-code
Cool links & research papers related to Machine Learning applied to source code (MLonCode)
dennybritz/deeplearning-papernotes
Summaries and notes on Deep Learning research papers
owainlewis/awesome-artificial-intelligence
A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.
bharathgs/Awesome-pytorch-list
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
zziz/pwc
This repository is no longer maintained.
terryum/awesome-deep-learning-papers
The most cited deep learning papers
floodsung/Deep-Learning-Papers-Reading-Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
papers-we-love/papers-we-love
Papers from the computer science community to read and discuss.
Cloud-CV/EvalAI
:cloud: :rocket: :bar_chart: :chart_with_upwards_trend: Evaluating state of the art in AI
YapengTian/Single-Image-Super-Resolution
A collection of high-impact and state-of-the-art SR methods
onnx/models
A collection of pre-trained, state-of-the-art models in the ONNX format
wenbihan/reproducible-image-denoising-state-of-the-art
Collection of popular and reproducible image denoising works.
RedditSota/state-of-the-art-result-for-machine-learning-problems
This repository provides state of the art (SoTA) results for all machine learning problems. We do our best to keep this repository up to date. If you do find a problem's SoTA result is out of date or missing, please raise this as an issue or submit Google form (with this information: research paper name, dataset, metric, source code and year). We will fix it immediately.
yu4u/noise2noise
An unofficial and partial Keras implementation of "Noise2Noise: Learning Image Restoration without Clean Data"
pfnet-research/chainer-gan-lib
Chainer implementation of recent GAN variants
wesm/pydata-book
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
donnemartin/data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
jakevdp/PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks