fastbook | The fastai book , published as Jupyter Notebooks | Machine Learning library

 by   fastai Jupyter Notebook Version: 0.0.29 License: Non-SPDX

kandi X-RAY | fastbook Summary

kandi X-RAY | fastbook Summary

fastbook is a Jupyter Notebook library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. fastbook has no bugs, it has no vulnerabilities and it has medium support. However fastbook has a Non-SPDX License. You can download it from GitHub.

These notebooks cover an introduction to deep learning, fastai, and PyTorch. fastai is a layered API for deep learning; for more information, see the fastai paper. Everything in this repo is copyright Jeremy Howard and Sylvain Gugger, 2020 onwards. These notebooks are used for a MOOC and form the basis of this book, which is currently available for purchase. It does not have the same GPL restrictions that are on this draft. The code in the notebooks and python .py files is covered by the GPL v3 license; see the LICENSE file for details. The remainder (including all markdown cells in the notebooks and other prose) is not licensed for any redistribution or change of format or medium, other than making copies of the notebooks or forking this repo for your own private use. No commercial or broadcast use is allowed. We are making these materials freely available to help you learn deep learning, so please respect our copyright and these restrictions. If you see someone hosting a copy of these materials somewhere else, please let them know that their actions are not allowed and may lead to legal action. Moreover, they would be hurting the community because we're not likely to release additional materials in this way if people ignore our copyright. This is an early draft. If you get stuck running notebooks, please search the fastai-dev forum for answers, and ask for help there if needed. Please don't use GitHub issues for problems running the notebooks. If you make any pull requests to this repo, then you are assigning copyright of that work to Jeremy Howard and Sylvain Gugger. (Additionally, if you are making small edits to spelling or text, please specify the name of the file and a very brief description of what you're fixing. It's difficult for reviewers to know which corrections have already been made. Thank you.).

            kandi-support Support

              fastbook has a medium active ecosystem.
              It has 18615 star(s) with 7101 fork(s). There are 497 watchers for this library.
              There were 1 major release(s) in the last 12 months.
              There are 78 open issues and 138 have been closed. On average issues are closed in 119 days. There are 34 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of fastbook is 0.0.29

            kandi-Quality Quality

              fastbook has 0 bugs and 0 code smells.

            kandi-Security Security

              fastbook has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              fastbook code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              fastbook has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

            kandi-Reuse Reuse

              fastbook releases are available to install and integrate.
              Installation instructions are not available. Examples and code snippets are available.
              It has 99 lines of code, 13 functions and 2 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

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            fastbook Key Features

            No Key Features are available at this moment for fastbook.

            fastbook Examples and Code Snippets

            No Code Snippets are available at this moment for fastbook.

            Community Discussions


            Attribute Error: `loss.backward()` returns None
            Asked 2022-Feb-17 at 18:30

            I'm trying to implement the Learner object and its steps and facing an issue with the loss.backward() function as it raises and AttributeError: 'NoneType' object has no attribute 'data'

            The entire process works when I follow the Chapter 04 MNIST Basics. However, implementing within a class raises this error. Could anybody guide me on why this occurs and ways to fix this?

            Here's the code below:



            Answered 2022-Feb-17 at 18:30

            It seems like your optimizer and your trainer do not work on the same model.
            You have model=simple_net, while the parameters for the optimizer are those of a different model params=linear_model.parameters().

            Try passing params=simple_net.parameters() -- that is, make sure the trainer's params are those of model.



            Fast Ai: AttributeError: 'Learner' object has no attribute 'fine_tune'
            Asked 2020-Dec-08 at 13:47

            Fast Ai uses a very unconventional style of from fastai import * etc.

            I for one do not like it so was painstakingly identifying each import in the chapter 2 of the fastai book but ran into the error



            Answered 2020-Dec-08 at 13:25

            I just faced the exact same issue. After looking at one of their tutorial I saw that the cnn learner is not imported from the expected package.



            Fast AI pulling a fast one?
            Asked 2020-Dec-04 at 23:08

            Normally statements like from module import * are frowned upon by expert python programmers as they can lead to namespace clobbering. Yet they are frequent in Fast AI and the justification is that it makes life simpler for the student. Below is an excerpt from their book

            This may be so and as long as it is simply a matter of importing everything that's fine I guess.

            However, below we will see that it does more than a simple import and an instance of a cnn_learner that has no method called fine_tune ends up having one when we run from import *.



            Answered 2020-Dec-04 at 23:07

            One alternate approach to from import * is



            pip install options unclear
            Asked 2020-Oct-11 at 12:50

            I saw this on jupyter notebook



            Answered 2020-Oct-11 at 12:50

            The option -q of pip give less output.

            The Option is additive. In other words, you can use it up to 3 times (corresponding to WARNING, ERROR, and CRITICAL logging levels).


            • -q means display only the messages with WARNING,ERROR,CRITICAL log levels
            • -qq means display only the messages with ERROR,CRITICAL log levels
            • -qqq means display only the messages with CRITICAL log level


            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install fastbook

            You can download it from GitHub.


            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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            pip install fastbook

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