The 3rd edition of course.fast.ai
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Updated
Oct 1, 2020 - Jupyter Notebook
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The 3rd edition of course.fast.ai
The fastai book, published as Jupyter Notebooks
Starter app for fastai v3 model deployment on Render
An easy to use blogging platform, with enhanced support for Jupyter Notebooks.
A site that displays up to date COVID-19 stats, powered by fastpages.
Super easy library for BERT based NLP models
Temporary home for fastai v2 while it's being developed
Create delightful python projects using Jupyter Notebooks
Code For Medium Article: "How To Create Natural Language Semantic Search for Arbitrary Objects With Deep Learning"
Plant Disease Detector Web Application
Python supercharged for the fastai library
Deep Learning model to classify food (Web App)
Practical Deep Learning for Time Series / Sequential Data library based on fastai v2/ Pytorch
An API for identifying cougars v.s. bobcats v.s. other USA cat species
Food detection and recommendation with deep learning
The code to reproduce results from paper "MultiFiT: Efficient Multi-lingual Language Model Fine-tuning" https://arxiv.org/abs/1909.04761
Deploy your Flask web app classifier on Heroku which is written using fastai library.
Contents covered in sessions of AI Saturdays (cycle 2) as well as relevant material for further study.
Docker environment for fast.ai Deep Learning Course 1 at http://course.fast.ai
中文ULMFiT 情感分析 文本分类
Some experiments with object detection in PyTorch
Convolutional Neural Network for German Traffic Sign Recognition Benchmark
Fast.AI course complete docker container for Paperspace and Gradient
Thank you for helping us build this amazing library
The fastest way to learn the framework is by exploring the documentation and by playing around with the different tutorials (that are all available in colab).
The easiest way to start contributing is to start using the library and sharing your work with us (replying to this thread).
Fast.AI course complete docker container for Paperspace and Gradient
Add a description, image, and links to the fastai topic page so that developers can more easily learn about it.
To associate your repository with the fastai topic, visit your repo's landing page and select "manage topics."
The code in
autofocus/predictworks, but it was written in a hurry and would probably benefit from some careful attention.