|4 days ago||4 days ago|
|BSD 1-Clause License||GNU General Public License v3.0 or later|
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Building a powerful deep learning workstation
1 project | reddit.com/r/buildapcforme | 29 Nov 2021
We will do no gaming whatsoever. The jobs will focus on training deep-learning models, for which we will predominantly use pytorch, which runs on CUDA. We will *exclusively* handle image data, which may come in scales of MB per image ranging until TB per image, hence, fast file transfer speeds from mainboard/storage to GPU is very important. Some of the data may have to be copied from an external fileserver, and then be stored temporarily on the local drives for processing. Thus, we also need high file transfer through the LAN connection.
Nvidia Ceo- Jensen on competition from Amd.
1 project | reddit.com/r/Amd | 23 Nov 2021
One of my coworkers managed to get pytorch working with AMD but it took him a week to get everything working properly (which in itself was surprising given previous history). And that's with the current driver + library version stack -- who knows what it's going to be like in 6 months time, half the time to get this stuff working you're following some guy's side project on github that he could get bored with and stop supporting at any point.
Why Can't PyTorch Find Cuda?
1 project | reddit.com/r/learnpython | 16 Nov 2021
I installed PyTorch with CUDA like the PyTorch website recommended:
PyTorch to Support Apple M1 GPU
1 project | news.ycombinator.com | 15 Nov 2021
PyTorch set to support Apple M1 GPU
1 project | news.ycombinator.com | 15 Nov 2021
PyTorch Fortran Bindings
3 projects | news.ycombinator.com | 14 Nov 2021
Data Science toolset summary from 2021
13 projects | dev.to | 13 Nov 2021
PyTorch - PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing, primarily developed by Facebook's AI Research lab. It is free and open-source software released under the Modified BSD license. Link - https://pytorch.org/
Main PyTorch maintainer confirms that work is being done to support Apple Silicon GPU acceleration for the popular machine learning framework.
2 projects | reddit.com/r/apple | 10 Nov 2021
[Project] JORLDY: OpenSource Reinforcement Learning Framework
1 project | reddit.com/r/MachineLearning | 8 Nov 2021
20+ RL Algorithms (Pytorch) and various RL environment are provided
How to install PyTorch using m1 max macbook pro?
2 projects | reddit.com/r/pytorch | 1 Nov 2021
Which is the best Rust scripting language for Exploratory Data Analysis (EDA)
7 projects | reddit.com/r/rust | 9 Oct 2021
The syntax is lightweight (at least in my opinion), there's support for Jupyter, a decent range of visualization packages are available, as are bindings to Spark and Torch. Flux is recommended over using bindings to TensorFlow though. It's possible to create Julia arrays backed directly by data from Rust with jlrs (though the data must be in column-major order), and borrow Julia array data as an ArrayView(Mut) by enabling the jlrs-ndarray feature.
Should you learn Julia or Python for Machine Learning?
8 projects | reddit.com/r/learnmachinelearning | 15 Aug 2021
We used to use the popular Flux, Knet, MLBase, and Plots packages for Machine Learning in Julia.
Project in julia
3 projects | reddit.com/r/Julia | 12 Aug 2021
You can also do some deep learning in Julia if you like. Flux.jl is Julia's deep learning library, and they have a model zoo of easy to follow working examples as a good starting point.
Fastai.jl: Fastai for Julia
6 projects | news.ycombinator.com | 27 Jul 2021
Transformers.jl and TextAnalysis.jl already provide quite a bit of functionality for NLP, though to my knowledge neither makes use of RNNs. You may be interested in commenting on https://github.com/FluxML/Flux.jl/issues/1678.
Julia: faster than Fortran, cleaner than Numpy
4 projects | reddit.com/r/programming | 21 Jun 2021
My advice would be to use Python for deep learning for now but keep watching the development of deep learning in Julia. For instance, there is an effort to achieve feature parity with PyTorch in Flux.jl. I believe Julia will be more than a viable language for deep learning in near future.
Neural networks with automatic differentiation.
3 projects | reddit.com/r/Julia | 13 Apr 2021
I believe you are referring to https://github.com/FluxML/Flux.jl which is exactly that, a machine learning lib with AD, the source code is very simple because of AD so you can browse it without much prior knowledge
Nearly 40, Doing a part time BSc in Math. Looking for cool stuff to do on my computer.
1 project | reddit.com/r/math | 4 Apr 2021
If you're feeling ambitious you could check out the Julia package Flux.
What are some alternatives?
tensorflow - An Open Source Machine Learning Framework for Everyone
ROCm - ROCm - Open Source Platform for HPC and Ultrascale GPU Computing
Caffe - Caffe: a fast open framework for deep learning.
Theano - Theano was a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It is being continued as aesara: www.github.com/pymc-devs/aesara
Keras - Deep Learning for humans
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
frugally-deep - Header-only library for using Keras models in C++.
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
Serpent.AI - Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!