mattfeng
"For my part I know nothing with any certainty, but the sight of the stars makes me dream." - Vincent Van Gogh
Massachusetts Institute of TechnologyCambridge, Massachusetts
mattfeng's Stars
soulmachine/machine-learning-cheat-sheet
Classical equations and diagrams in machine learning
bobeff/programming-math-science
This is a list of links to different freely available learning resources about computer programming, math, and science.
wookayin/python-imgcat
🖼 imgcat in Python (for iTerm2)
dabeaz-course/python-mastery
Advanced Python Mastery (course by @dabeaz)
mitmath/matrixcalc
MIT IAP short course: Matrix Calculus for Machine Learning and Beyond
pb3lab/ibm3202
Google Colab Tutorials for IBM3202
brettbode/wxmacmolplt
wxMacMolPlt is a graphical user interface principally for the GAMESS program
pbloem/former
Simple transformer implementation from scratch in pytorch.
mir-group/allegro
Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
AndresRicoM/MAIA
Taking Bio Sensors Out Of The Lab. Modular , low-cost,
agemagician/ProtTrans
ProtTrans is providing state of the art pretrained language models for proteins. ProtTrans was trained on thousands of GPUs from Summit and hundreds of Google TPUs using Transformers Models.
thunlp/GNNPapers
Must-read papers on graph neural networks (GNN)
nschloe/purple-pi
:purple_heart: LaTeX math wherever you want
widdowquinn/ten_great_papers
Ten great papers for wet lab biologists starting out in computational biology
google-deepmind/alphafold
Open source code for AlphaFold.
ikostrikov/pytorch-a2c-ppo-acktr-gail
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
enggen/DeepMind-Advanced-Deep-Learning-and-Reinforcement-Learning
Advanced Deep Learning and Reinforcement Learning course taught at UCL in partnership with Deepmind
ctallec/world-models
Reimplementation of World-Models (Ha and Schmidhuber 2018) in pytorch
kubeflow/pytorch-operator
PyTorch on Kubernetes
garris/BackstopJS
Catch CSS curve balls.
danijar/dreamer
Dream to Control: Learning Behaviors by Latent Imagination
rlabbe/Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
danielfm/prometheus-for-developers
Practical introduction to Prometheus for developers.
TylerBrock/mongo-hacker
MongoDB Shell Enhancements for Hackers
alok/notational-fzf-vim
Notational velocity for vim.
kdeldycke/awesome-falsehood
😱 Falsehoods Programmers Believe in
bradtraversy/design-resources-for-developers
Curated list of design and UI resources from stock photos, web templates, CSS frameworks, UI libraries, tools and much more
parrt/bookish
A tool that translates augmented markdown into HTML or latex
hobby-kube/guide
Kubernetes clusters for the hobbyist.
scutan90/DeepLearning-500-questions
深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,50余万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系scutjy2015@163.com 版权所有,违权必究 Tan 2018.06