imsrgadich's Stars
serhii-londar/open-source-mac-os-apps
🚀 Awesome list of open source applications for macOS. https://t.me/s/opensourcemacosapps
posquit0/Awesome-CV
:page_facing_up: Awesome CV is LaTeX template for your outstanding job application
horovod/horovod
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
allenai/allennlp
An open-source NLP research library, built on PyTorch.
clips/pattern
Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.
docker/docker-py
A Python library for the Docker Engine API
cleverhans-lab/cleverhans
An adversarial example library for constructing attacks, building defenses, and benchmarking both
tensorflow/probability
Probabilistic reasoning and statistical analysis in TensorFlow
Quartz/bad-data-guide
An exhaustive reference to problems seen in real-world data along with suggestions on how to resolve them.
tox-dev/pipdeptree
A command line utility to display dependency tree of the installed Python packages
sux13/DataScienceSpCourseNotes
Compiled Notes for all 9 courses in the Coursera Data Science Specialization
databricks/tensorframes
[DEPRECATED] Tensorflow wrapper for DataFrames on Apache Spark
kakao/n2
TOROS N2 - lightweight approximate Nearest Neighbor library which runs fast even with large datasets
wwkenwong/book
hoangcuong2011/Good-Papers
I try my best to keep updated cutting-edge knowledge in Machine Learning/Deep Learning and Natural Language Processing. These are my notes on some good papers
SheffieldML/PyDeepGP
Deep Gaussian Processes in Python
marionmari/pyGPs
pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.
sdrogers/fcmlcode
Riashat/Deep-Bayesian-Active-Learning
Code for Deep Bayesian Active Learning (ICML 2017)
jingweiz/pytorch-distributed
Ape-X DQN & DDPG with pytorch & tensorboard
maka89/Deep-Kernel-GP
Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood
ssydasheng/Neural-Kernel-Network
Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
duvenaud/deep-limits
Repo for a paper about constructing priors on very deep models.
aboustati/dgplib
Library for Deep Gaussian Processes based on GPflow
ssydasheng/GPflow-Slim
customized GPflow with simple Tensorflow API
ayushi-b/Random_Phenomena_by_Babatunde_Ogunnaike
📖 Solutions of exercises from the book "Random Phenomena: Fundamentals of Probability and Statistics for Engineers" by Babatunde Ogunnaike.
hegdepashupati/gprn-svi
Implementation for Stovhastic Variational Inference for following models :Gaussian Process Regression Netwroks (Wilson, 2011) and Sparse GPRN
adezfouli/Structured_GP
Structured Gaussian Process
cdipaolo/GPy
Gaussian processes framework in python
st--/prettyplotlib
Painlessly create beautiful matplotlib plots.