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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:

Documentation. Search ... Visualize, track, and compare Fastai models: A thoroughly documented walkthrough

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.

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.

Kaggle recently enacted a notebooks abuse countermeasure which resulted in a large number of false account blocks. We have corrected the issue and are ...

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 simplifies training fast and accurate neural nets using modern best practices. ... See the fast.ai documentation on Using Colab for more information.

​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 ...

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 …

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.

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.

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.

Algorithms. Please read the papers or blog posts before getting started with an algorithm, you may also check out documentation page of ...

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 ...

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.

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 ...

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 ...

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.

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.

Interactive API docs¶. Now go to http://127.0.0.1:8000/docs. You will see the automatic interactive API documentation (provided by ...

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.