专栏名称: 机器学习研究会

机器学习研究会是北京大学大数据与机器学习创新中心旗下的学生组织，旨在构建一个机器学习从事者交流的平台。除了及时分享领域资讯外，协会还会举办各种业界巨头/学术神牛讲座、学术大牛沙龙分享会、real data 创新竞赛等活动。

【推荐】Google 研究员、Keras 作者Francois Chollet书籍《Python深度学习》

机器学习研究会 · 公众号 · AI · 2017-01-29 21:21

正文

点击上方 “机器学习研究会” 可以订阅哦

摘要

转自：爱可可-爱生活&AI100

《Deep Learning with Python》的作者是 Google 的研究员，开源深度学习框架 Keras 的作者 Francois Chollet，书中通过用 Python 解决现实中的问题为线索来展开，包括：图像分类、语音识别、问答系统、OCR 等等任务。Keras 是一个非常简单易用的二次框架，以 Theano 和 Tensorflow 为底层框架，使用风格与 Torch 类似。

Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and optical character recognition. It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.

In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.