|5 days ago||about 2 months ago|
|MIT License||Apache License 2.0|
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.
There is framework for everything.
107 projects | reddit.com/r/ProgrammerHumor | 4 Aug 2022
This Week in Python
5 projects | dev.to | 1 Apr 2022
recommenders – Best Practices on Recommendation Systems
Input to SVD, SAR, NMF
1 project | reddit.com/r/learnmachinelearning | 14 Mar 2022
I would like to do a benchmarking on the Microsoft models SVD, SAR and NMF (available here: https://github.com/microsoft/recommenders) but with this input data I get a precision and recall close to zero. Any ideas how I can improve this? For SVD and NMF (surprise library) the model wants a rating input that is normally distributed, which it not the case for my binary data where the transactions all have a rating of 1.
Opinion on choice of model - Recommender System
2 projects | reddit.com/r/datascience | 10 Apr 2021
Then I tried to find some more advanced models and I found this really good list and in there I found the Microsoft one. So it's' where we are now, which a bunch of different models and not a documentation/tutorials out there.
Please comment on my planned research project structure
1 project | reddit.com/r/learnpython | 7 Jun 2022
Under the hood, the ModelWrapper object will create a ML model based on the config (so far, an XGBoost model and a PyTorch Lightning model). Each of those will have a wrapper that conducts training and evaluation (since from my understanding of Lightning, Trainers are required to be outside of the class). In lack of a better name, I call these wrappers Fitters. For uniformity, I thought about adding a common interface IFitter, which is inherited by all model wrappers as outlined below.
Watch out for the (PyTorch) Lightning
1 project | dev.to | 2 May 2022
Join their Slack to ask the community questions and check out the GitHub here.
[P] Composer: a new PyTorch library to train models ~2-4x faster with better algorithms
7 projects | reddit.com/r/MachineLearning | 16 Mar 2022
Pytorch lightning benchmarks against pytorch on every PR (benchmarks to make sure that it is mot slower.
[D] What Repetitive Tasks Related to Machine Learning do You Hate Doing?
4 projects | reddit.com/r/MachineLearning | 21 Feb 2022
There is already a ton of momentum around automating ML workflows. I would suggest you contribute to a preexisting project like, for instance, PyTorch Lightning or fast.ai.
1 project | news.ycombinator.com | 10 Feb 2022
[D] Are you using PyTorch or TensorFlow going into 2022?
6 projects | reddit.com/r/MachineLearning | 14 Dec 2021
Is the problem the sheer number of options, or the fact that they are all together in one place? Would it be better if they were organized into the different trainer entrypoints (fit, validate, ...)? If that is the case, there was an RFC proposing this which you might find interesting, feel free to drop by and comment on the issue: https://github.com/PyTorchLightning/pytorch-lightning/issues/10444
[D] Colab TPU low performance
2 projects | reddit.com/r/MachineLearning | 18 Nov 2021
I wanted to make a quick performance comparison between the GPU (Tesla K80) and TPU (v2-8) available in Google Colab with PyTorch. To do so quickly, I used an MNIST example from pytorch-lightning that trains a simple CNN.
[D] How to avoid CPU bottlenecking in PyTorch - training slowed by augmentations and data loading?
2 projects | reddit.com/r/MachineLearning | 10 Nov 2021
We've noticed GPU 0 on our 3 GPU system is sometimes idle (which would explain performance differences). However its unclear to us why that may be. Similar to this issue
[P] An introduction to PyKale https://github.com/pykale/pykale, a PyTorch library that provides a unified pipeline-based API for knowledge-aware multimodal learning and transfer learning on graphs, images, texts, and videos to accelerate interdisciplinary research. Welcome feedback/contribution!
2 projects | reddit.com/r/MachineLearning | 25 Apr 2021
If you want a good example for reference, take a look at Pytorch Lightning's readme (https://github.com/PyTorchLightning/pytorch-lightning) It answers the 3 questions of "what is this", "why should I care", and "how do i use it" almost instantly
2 projects | reddit.com/r/pytorch | 24 Apr 2021
What are some alternatives?
mmdetection - OpenMMLab Detection Toolbox and Benchmark
detectron2 - Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
pytorch-grad-cam - Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
sparktorch - Train and run Pytorch models on Apache Spark.
Keras - Deep Learning for humans
fastai - The fastai deep learning library
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
ffcv - FFCV: Fast Forward Computer Vision (and other ML workloads!)
composer - Train neural networks up to 7x faster
metaflow - :rocket: Build and manage real-life data science projects with ease!
pytorch-forecasting - Time series forecasting with PyTorch
omegaconf - Flexible Python configuration system. The last one you will ever need.