Deep learning has the reputation as an exclusive domain for math PhDs. Not so. With this book, programmers comfortable with Python will learn how to get started with deep learning right away. Using PyTorch and the fastai deep learning library, you’ll learn how to train a model to accomplis...
很多人认为,要在深度学习中取得优秀的结果,你需要各种难以找到的东西,但正如你在本书中所看到的,这些人是错的。表1-1列出了世界级深度学习中绝对不需要的一些东西。 表1-1。深度学习中你不需要的东西 深度学习是一种计算机技术,通过使用多层神经网络来提取和转换数据,应用案例从人类语音识别到动物图像分类不一而...
Deep Learning for Coders with fastai and PyTorch 星级: 405 页 Deep Learning with PyTorch 星级: 360 页 Deep Learning with PyTorch 星级: 408 页 Deep Learning with PyTorch 星级: 357 页 Deep Learning with PyTorch 星级: 287 页 Deep Learning with PyTorch 星级: 255 页 Deep Learning with...
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results … - Selection from Deep Learning for Coders with fast
1. Lesson 1 - Deep Learning for Coders (2020)是【Deep Learning for Coders with fastai and PyTorch】深度学习初学者入门好著作,原著作者带你一起啃透这本书!!!的第1集视频,该合集共计9集,视频收藏或关注UP主,及时了解更多相关视频内容。
Chapter 4. Under the Hood: Training a Digit Classifier Having seen what it looks like to train a variety of models in Chapter 2, let’s now look under the … - Selection from Deep Learning for Coders with fastai and PyTorch [Book]
Deep Learning for Coders with fastai and PyTorch by Jeremy Howard and Sylvain Gugger Deep learning is not only a rapidly evolving field, but it’s also becoming more accessible. Thanks to the development of intuitive, user-friendly libraries and interfaces, it’s no longer necessary to have a...
Deep Learning for Coders, 2020, the website. Contribute to fastai/course20 development by creating an account on GitHub.
@book{howard2020deep, title={Deep Learning for Coders with Fastai and Pytorch: AI Applications Without a PhD}, author={Howard, J. and Gugger, S.}, isbn={9781492045526}, url={https://books.google.no/books?id=xd6LxgEACAAJ}, year={2020}, publisher={O'Reilly Media, Incorporated} } ...
(自学《Deep-Learning-with-PyTorch》使用,仅供参考) 1.对于部署模型,本书中主要使用了两个轻量级Python web框架:Flask(http://flask.pocoo.org)和Sanic(https://sanicframework.org)。 Flask是最流行的框架,而Sanic和Flask本质上相同,但比Flask多了一个对Python中async/await的异步操作,提高了效率。