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https://github.com/unixomg/python-doc/blob/master/Python Weekly/Python_Weekly_Issue_293.md#来自赞助商
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https://github.com/unixomg/python-doc/blob/master/Python Weekly/Python_Weekly_Issue_293.md#文章教程和讲座
使用计算机视觉和深度学习创建现代OCR管道https://blogs.dropbox.com/tech/2017/04/creating-a-modern-ocr-pipeline-using-computer-vision-and-deep-learning/
使用Python和SciKit Learn 0.18的神经网络初学者指南https://www.springboard.com/blog/beginners-guide-neural-network-in-python-scikit-learn-0-18/
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使用Faker,为Python单元测试创建假数据https://semaphoreci.com/community/tutorials/generating-fake-data-for-python-unit-tests-with-faker
关于Django中的预取(prefetching),你所需要知道的一切https://hackernoon.com/all-you-need-to-know-about-prefetching-in-django-f9068ebe1e60
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如何使用Keras和Tensorflow中的传递学习和微调,来构建构建一个图像识别系统,并分类(几乎)任何对象https://deeplearningsandbox.com/how-to-use-transfer-learning-and-fine-tuning-in-keras-and-tensorflow-to-build-an-image-recognition-94b0b02444f2
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利用流行建模来改善Facebook上的广告点击率https://medium.com/towards-data-science/utilising-epidemic-modelling-to-improve-advertising-click-rates-on-facebook-6f294205a43f
https://github.com/unixomg/python-doc/blob/master/Python Weekly/Python_Weekly_Issue_293.md#本周的python工作
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https://github.com/unixomg/python-doc/blob/master/Python Weekly/Python_Weekly_Issue_293.md#好玩的项目工具和库
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https://github.com/unixomg/python-doc/blob/master/Python Weekly/Python_Weekly_Issue_293.md#近期活动和网络研讨会
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