The State of Machine Learning Frameworks in 2019
By Horace He : https://thegradient.pub/state-of-ml-frameworks-2019-pytorch-dominates-research-tensorflow-dominates-industry/
#MachineLearning #PyTorch #TensorFlow

Benchmarking Every Open Source Model
By Papers With Code : https://sotabench.com
#DeepLearning #PyTorch #TensorFlow https://t.me/ArtificialIntelligenceArticles

BoTorch: Programmable Bayesian Optimization in PyTorch
Balandat et al.: https://arxiv.org/abs/1910.06403
Code: https://github.com/pytorch/botorch
#MachineLearning #Bayesian #PyTorch

🎓 Reinforcement Learning Course from OpenAI

Reinforcement Learning becoming significant part of the data scientist toolbox.
OpenAI created and published one of the best courses in #RL. Algorithms implementation written in #Tensorflow.
But if you are more comfortable with #PyTorch, we have found #PyTorch implementation of this algs

OpenAI Course: https://spinningup.openai.com/en/latest/
Tensorflow Code: https://github.com/openai/spinningup
PyTorch Code: https://github.com/kashif/firedup

#MOOC #edu #course #OpenAI

GPyTorch
Gaussian processes for modern machine learning systems.
GitHub: https://github.com/cornellius-gp/gpytorch
Website: https://gpytorch.ai
#PyTorch #NeuralNetworks #MachineLearning

@ArtificialIntelligenceArticles

Pytorch-Struct
Fast, general, and tested differentiable structured prediction in PyTorch. By Harvard NLP : https://github.com/harvardnlp/pytorch-struct
#PyTorch #DeepLearning #ArtificialIntelligence

"Differentiable Convex Optimization Layers"
CVXPY creates powerful new PyTorch and TensorFlow layers
Agrawal et al.: https://locuslab.github.io/2019-10-28-cvxpylayers/
#PyTorch #TensorFlow #NeurIPS2019

Connections between Support Vector Machines, Wasserstein distance and gradient-penalty GANs
Alexia Jolicoeur-Martineau, Ioannis Mitliagkas : https://arxiv.org/abs/1910.06922
#PyTorch code: https://github.com/AlexiaJM/MaximumMarginGANs
#SupportVectorMachines #GenerativeAdversarialNetworks

We just released our #NeurIPS2019 Multimodal Model-Agnostic Meta-Learning (MMAML) code for learning few-shot image classification, which extends MAML to multimodal task distributions (e.g. learning from multiple datasets). The code contains #PyTorch implementations of our model and two baselines (MAML and Multi-MAML) as well as the scripts to evaluate these models to five popular few-shot learning datasets: Omniglot, Mini-ImageNet, FC100 (CIFAR100), CUB-200-2011, and FGVC-Aircraft.

Code: https://github.com/shaohua0116/MMAML-Classification

Paper: https://arxiv.org/abs/1910.13616

#NeurIPS #MachineLearning #ML #code

PyTorch: An Imperative Style, High-Performance Deep Learning Library
Paszke et al.: https://arxiv.org/abs/1912.01703
#ArtificialIntelligence #deepLearning #PyTorch

"Differentiable Convex Optimization Layers"
CVXPY creates powerful new PyTorch and TensorFlow layers
Agrawal et al.: https://locuslab.github.io/2019-10-28-cvxpylayers/
#PyTorch #TensorFlow #NeurIPS2019

"Differentiable Convex Optimization Layers"
CVXPY creates powerful new PyTorch and TensorFlow layers
Agrawal et al.: https://locuslab.github.io/2019-10-28-cvxpylayers/
#PyTorch #TensorFlow #NeurIPS2019

PyTorch: An Imperative Style, High-Performance Deep Learning Library
Paszke et al.: https://arxiv.org/abs/1912.01703
#ArtificialIntelligence #DeepLearning #PyTorch

Machine Learning Unlocks Library of The Human Brain. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #NeuroScience


http://thetartan.org/2019/11/11/scitech/brain-thoughts

PyTorch Geometry
The PyTorch Geometry package is a geometric computer vision library for PyTorch
By Arraiy: https://github.com/arraiy/torchgeometry
#ArtificialIntelligence #ComputerVision #DeepLearning #MachineLearning #PyTorch

PyTorch Wrapper version 1.1 is out!

New Features:

- Samplers for smart batching based on text length for faster training.

- Loss and Evaluation wrappers for token prediction tasks.

- New nn.modules for attention based models.

- Support for multi GPU training / evaluation / prediction.

- Verbose argument in system's methods.

- Examples using Transformer based models like BERT for text classification.

Check it out in the following links:

install with: pip install pytorch-wrapper

GitHub: https://github.com/jkoutsikakis/pytorch-wrapper

docs: https://pytorch-wrapper.readthedocs.io/en/latest/

examples: https://github.com/jkouts…/pytorch-wrapper/…/master/examples

#DeepLearning #PyTorch #NeuralNetworks #MachineLearning #DataScience #python #TensorFlow

PyTorch internals
http://blog.ezyang.com/2019/05/pytorch-internals/
#ArtificialIntelligence #DeepLearning #Pytorch

RLlib: Scalable Reinforcement Learning
RLlib is an open-source library for reinforcement learning that offers both high scalability and a unified API for a variety of applications.
RLlib natively supports TensorFlow, TensorFlow Eager, and PyTorch, but most of its internals are framework agnostic.
The Ray Team : https://ray.readthedocs.io/en/latest/rllib.html
#ReinforcementLearning #PyTorch #TensorFlow

MiniTorch
Sasha Rush and Ge Gao : https://minitorch.github.io/index.html
#DeepLearning #PyTorch #Python

Enzyme, a compiler plug-in for importing foreign code into systems like TensorFlow & PyTorch without having to rewrite it. v/@MIT_CSAIL

Paper: http://bit.ly/EnzymePDF

More: http://bit.ly/EnzymeML

#ML #MachineLearning #PyTorch #TensorFlowJS #NeurIPS #tensorflow #AI