4iar's Stars
CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
eriklindernoren/ML-From-Scratch
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
zziz/pwc
This repository is no longer maintained.
alyssaxuu/flowy
The minimal javascript library to create flowcharts ✨
nbedos/termtosvg
Record terminal sessions as SVG animations
kjw0612/awesome-rnn
Recurrent Neural Network - A curated list of resources dedicated to RNN
p-christ/Deep-Reinforcement-Learning-Algorithms-with-PyTorch
PyTorch implementations of deep reinforcement learning algorithms and environments
pytorch/ignite
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
system-f/fp-course
Functional Programming Course
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).
cliffe/SecGen
Create randomly insecure VMs
krzjoa/awesome-python-data-science
Probably the best curated list of data science software in Python.
tirthajyoti/Papers-Literature-ML-DL-RL-AI
Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning
joshnewlan/say_what
Using speech-to-text to fully check out during con calls
rougier/from-python-to-numpy
An open-access book on numpy vectorization techniques, Nicolas P. Rougier, 2017
rlworkgroup/garage
A toolkit for reproducible reinforcement learning research.
solo-io/squash
The debugger for microservices
glumpy/glumpy
Python+Numpy+OpenGL: fast, scalable and beautiful scientific visualization
easystats/easystats
:milky_way: The R easystats-project
easystats/performance
:muscle: Models' quality and performance metrics (R2, ICC, LOO, AIC, BF, ...)
csinva/csinva.github.io
Slides, paper notes, class notes, blog posts, and research on ML 📉, statistics 📊, and AI 🤖.
r-causal/ggdag
:arrow_lower_left: :arrow_lower_right: An R package for working with causal directed acyclic graphs (DAGs)
guillaume-chevalier/Spiking-Neural-Network-SNN-with-PyTorch-where-Backpropagation-engenders-STDP
What about coding a Spiking Neural Network using an automatic differentiation framework? In SNNs, there is a time axis and the neural network sees data throughout time, and activation functions are instead spikes that are raised past a certain pre-activation threshold. Pre-activation values constantly fades if neurons aren't excited enough.
SilasX/git-upstage
Take credit for someone else's work; or, a typo gone too far.
ChrisPenner/wc
Beating unix `wc` in Haskell
holtzy/Pimp-my-rmd
A few tips about R markdown
takyamamoto/BNN-ANN-papers
Papers : Biological and Artificial Neural Networks
elastic/eui
Elastic UI Framework 🙌
reconmaster/ki_repo
Optimizing the repo
kevin-allen/relectro
R package to perform analysis of electrophysiological data.