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fastai documentation

fastai v1 - Documentation
docs.wandb.ai › integrations › fastai
Note: this documentation is for fastai v1. If you use the current version of fastai, you should refer to fastai page . For scripts using fastai v1, we have a callback that can automatically log model topology, losses, metrics, weights, gradients, sample predictions and best trained model.
| fastai
https://fastai1.fast.ai
05.01.2021 · fastai is designed to support both interactive computing as well as traditional software development. For interactive computing, where convenience and speed of experimentation is a priority, data scientists often prefer to grab all the symbols they need, with import *.Therefore, fastai is designed to support this approach, without compromising on …
Self Supervised Learning with Fastai | self_supervised
https://keremturgutlu.github.io › se...
Algorithms. Please read the papers or blog posts before getting started with an algorithm, you may also check out documentation page of ...
Tutorials | fastai
https://docs.fast.ai/tutorial
16.09.2021 · For tutorials, you can play around with the code and tweak it to do your own experiments. For the pages documenting the library, you will be able to see the source code and interact with all the tests. If you are just starting with the library, checkout the beginners tutorials. They cover how to treat each application using the high-level API:
fastai applications - quick start | fastai
https://docs.fast.ai/quick_start.html
29.11.2021 · fastai's applications all use the same basic steps and code: Create appropriate DataLoaders. Create a Learner. Call a fit method. Make predictions or view results. In this quick start, we'll show these steps for a wide range of difference applications and datasets. As you'll see, the code in each case is extremely similar, despite the very ...
Title | fastai
docs.fast.ai › data
Nov 07, 2021 · Documentation for the fastai library. fastai includes a replacement for Pytorch's DataLoader which is largely API-compatible, and adds a lot of useful functionality and flexibility.
Fastai - Documentation
https://docs.wandb.ai/guides/integrations/fastai
Documentation. Search ... Visualize, track, and compare Fastai models: A thoroughly documented walkthrough
Fastai - Documentation
docs.wandb.ai › integrations › fastai
whether we want to log our model (default to True). This also requires SaveModelCallback. log_dataset. False (default) True will log folder referenced by learn.dls.path. a path can be defined explicitly to reference which folder to log. Note: subfolder "models" is always ignored. dataset_name.
Title | fastai
https://docs.fast.ai/data.load.html
07.11.2021 · Documentation for the fastai library. fastai includes a replacement for Pytorch's DataLoader which is largely API-compatible, and adds a lot of useful functionality and flexibility. Before we look at the class, there are a couple of helpers we'll need to define.
| fastai
https://fastai1.fast.ai
Note: This documentation is all built from notebooks; that means that you can try any of the code you see in any notebook yourself! You'll find the notebooks in ...
FastAI.jl - Flux ML
https://fluxml.ai › FastAI.jl › dev
FastAI. Docs: Stable | Dev. FastAI.jl is inspired by fastai, and is a repository of best practices for deep learning in Julia. Its goal is to easily enable ...
fastai - documentation
docs.neptune.ai › model-training › fastai
fastai is a deep learning library that provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains and provides researchers with low-level components that can be mixed and matched to build new approaches.
Welcome to fastai | fastai
https://docs.fast.ai
07.11.2021 · About fastai. fastai is a deep learning library which provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains, and provides researchers with low-level components that can be mixed and matched to build new approaches.
Welcome to fastai | fastai
docs.fast.ai
Nov 07, 2021 · About fastai. fastai is a deep learning library which provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains, and provides researchers with low-level components that can be mixed and matched to build new approaches.
fastai - documentation - Neptune Docs
https://docs.neptune.ai › fastai
​fastai is a deep learning library that provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in ...
fastai v1 - Documentation
https://docs.wandb.ai/integrations/fastai/v1
Note: this documentation is for fastai v1. If you use the current version of fastai, you should refer to fastai page . For scripts using fastai v1, we have a callback that can automatically log model topology, losses, metrics, weights, gradients, sample predictions and best trained model.
FastAPI
https://fastapi.tiangolo.com
Interactive API docs¶. Now go to http://127.0.0.1:8000/docs. You will see the automatic interactive API documentation (provided by ...
fast.ai documentation | Data Science and Machine Learning
https://www.kaggle.com › question...
Kaggle recently enacted a notebooks abuse countermeasure which resulted in a large number of false account blocks. We have corrected the issue and are ...
fastai - documentation
https://docs.neptune.ai/integrations-and-supported-tools/model-training/fastai
fastai is a deep learning library that provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains and provides researchers with low-level components that can be mixed and matched to build new approaches.
Welcome to fastai | fastai
https://docs.fast.ai
fastai simplifies training fast and accurate neural nets using modern best practices. ... See the fast.ai documentation on Using Colab for more information.
Computer vision | fastai
https://docs.fast.ai/tutorial.vision.html
Using the fastai library in computer vision. The predict method returns three things: the decoded prediction (here False for dog), the index of the predicted class and the tensor of probabilities of all classes in the order of their indexed labels(in this case, the model is quite confifent about the being that of a dog). This method accepts a filename, a PIL image or a tensor directly in this ...