François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others.
Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects.
这本书从6月11号那天老板递到我手里,到今天刚好六周,在这期间我逐字逐句地啃了这本书,并在每周的周二和周五下午给组里的其他人讲这本书,每次讲3个小时。直到五分钟前刚刚讲完最后一章,写了175页的PPT。 感想从何谈起呢?先说Keras吧,这本书的作者是Keras的作者,所以本书...
评分 评分这本书从6月11号那天老板递到我手里,到今天刚好六周,在这期间我逐字逐句地啃了这本书,并在每周的周二和周五下午给组里的其他人讲这本书,每次讲3个小时。直到五分钟前刚刚讲完最后一章,写了175页的PPT。 感想从何谈起呢?先说Keras吧,这本书的作者是Keras的作者,所以本书...
只看了part2,虽然理论讲的不多,但绝不仅仅是keras in action,作者还列了很多基于自己经验觉得能work的trick,最后一章讲自己对deep learning未来的看法,跟软件工程结合起来也很有意思
评分keras 的接口好像还挺稳定的。
评分intro
评分1-4, 平庸,适合复习,不适合初学;5,transfer learning, visualization讲的很好,惜无semantic segmentation等高级话题;7,keras技巧,对于组建DAG型网有用,我的感受是这些技巧对阅读学术论文也有帮助
评分Keras作者的书,有些很有意思的例子,讲得不深,更像是Keras的代码示例,挺实用的,看完基本可以上手写了,里面套来解决各种常见问题的代码模板几乎都有。
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