fastai
ipyannotator
| fastai | ipyannotator | |
|---|---|---|
| 9 | 1 | |
| 25,638 | 34 | |
| 0.6% | - | |
| 8.0 | 0.0 | |
| 10 days ago | about 1 year ago | |
| Jupyter Notebook | Jupyter Notebook | |
| 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
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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.
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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 :)
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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.
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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
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Why noone uses nbdev for library development?
Development NB: https://github.com/fastai/fastai/blob/master/nbs/09_vision.augment.ipynb
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[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.
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Good practices for neural network training: identify, save, and document best models
If you are unaware of what fastai is, its official description is:
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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
ipyannotator
What are some alternatives?
pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]
ghapi - A delightful and complete interface to GitHub's amazing API
fastbook - The fastai book, published as Jupyter Notebooks
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
Watermark-Removal-Pytorch - 🔥 CNN for Watermark Removal using Deep Image Prior with Pytorch 🔥.
Universal Data Tool - Collaborate & label any type of data, images, text, or documents, in an easy web interface or desktop app.
PySyft - Perform data science on data that remains in someone else's server
nbdev - Create delightful software with Jupyter Notebooks
lego-mindstorms - My LEGO MINDSTORMS projects (using set 51515 electronics)
cvat - Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. [Moved to: https://github.com/opencv/cvat]
ru-dalle - Generate images from texts. In Russian
cvat - Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. [Moved to: https://github.com/cvat-ai/cvat]