fastai
pytorch-lightning
Our great sponsors
fastai | pytorch-lightning | |
---|---|---|
9 | 19 | |
25,610 | 19,188 | |
1.3% | - | |
8.0 | 9.9 | |
3 days ago | almost 2 years ago | |
Jupyter Notebook | Python | |
Apache License 2.0 | 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.
fastai
-
Cleared AWS Machine Learning - Specialty exam.. Happy to help!!!
Jeremy Howard's YouTube Channel - Jeremy maintains the fastai library, which is an excellent package that will help anyone build complicated ML architectures in minimum time. His YouTube Channel has a number of free courses which do an amazing job of covering a variety of ML topics, and he also maintains a very active forum for people studying ML.
-
Coding your own AI in 2023 with fastai
To create the AI we will use fastai. This is a python library, which is build on top of pytorch. No worries, you don't need to know how to code python. We will learn how this stuff works along the way :)
-
Fast.ai starts a corporate partnership program
You may know fast.ai as a popular deep learning course. There is also a deep learning library with the same name (https://github.com/fastai/fastai) as well as software development tools like nbdev (https://nbdev.fast.ai/).
fast.ai has been offering education and tools for free for over 7 years, and has been approached by many companies asking for help. This program offers an avenue for business to get relevant professional services and support.
-
People tricking ChatGPT “like watching an Asimov novel come to life”
The "fastai" course is free, and does a really nice job walking you through building simple neural nets from the ground up:
https://github.com/fastai/fastai
What's going on here is the exact same thing, just much, much larger.
- Programação letrada com Jupyter Notebook e Nbdev
-
Why noone uses nbdev for library development?
Development NB: https://github.com/fastai/fastai/blob/master/nbs/09_vision.augment.ipynb
-
[D] What Repetitive Tasks Related to Machine Learning do You Hate Doing?
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.
-
Good practices for neural network training: identify, save, and document best models
If you are unaware of what fastai is, its official description is:
-
D I Refuse To Use Pytorch Because Its A Facebook
Also, not a single docstring to document any code in the library - https://github.com/fastai/fastai/blob/master/fastai/vision/learner.py
pytorch-lightning
-
Problem with pytorch lightning and optuna with multiple callbacks
def on_validation_end(self, trainer: Trainer, pl_module: LightningModule) -> None: # Trainer calls `on_validation_end` for sanity check. Therefore, it is necessary to avoid # calling `trial.report` multiple times at epoch 0. For more details, see # https://github.com/PyTorchLightning/pytorch-lightning/issues/1391. if trainer.sanity_checking: return
-
Please comment on my planned research project structure
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
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
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?
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.
- PyTorch Lightening
-
[D] Are you using PyTorch or TensorFlow going into 2022?
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
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?
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!
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
What are some alternatives?
fastbook - The fastai book, published as Jupyter Notebooks
mmdetection - OpenMMLab Detection Toolbox and Benchmark
Watermark-Removal-Pytorch - 🔥 CNN for Watermark Removal using Deep Image Prior with Pytorch 🔥.
pytorch-grad-cam - Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
PySyft - Perform data science on data that remains in someone else's server
detectron2 - Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
lego-mindstorms - My LEGO MINDSTORMS projects (using set 51515 electronics)
composer - Supercharge Your Model Training
ru-dalle - Generate images from texts. In Russian
sparktorch - Train and run Pytorch models on Apache Spark.
pytorch-lightning - Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
Keras - Deep Learning for humans