解剖深度学习原理-从0编写深度学习库
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解剖深度学习原理
从0实现深度学习库
市面上的深度学习书要么晦涩难懂， 要么是平台使用说明书，只讲理论缺少实现或者只有编程缺少原理讲解，都很难让人理解深度学习的基本原理，本书采用理论讲解与代码实现的方式深入浅出地剖析了深度学习的技术原理和实现细节，教会读者如何从零编写一个深度学习库。内容包含了：梯度下降法、回归学习、前馈神经网络、卷积神经网络、循环神经网络、生成网络。
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市面上的深度学习书要么晦涩难懂，要么是平台使用说明书，只讲理论缺少实现或者只有编程缺少原理讲解，都很难让人理解深度学习的基本原理，本书采用理论讲解与代码实现的方式深入浅出地剖析了深度学习的技术原理和实现细节，教会读者如何从零编写一个深度学习库。内容包含了：梯度下降法、回归学习、前馈神经网络、卷积神经网络、循环神经网络、生成网络。
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本书深入浅出地介绍了深度学习的基本原理和实现过程，用python的numpy库从底层而不是借助于现有
的深度学习库从零构建了自己的深度学习库。在介绍基本的Python编程、微积分和概率统计知识基础
上，按照深度学习的发展脉络依次介绍了回归模型、神经网络、卷积神经网络、循环神经网络、生成网
络等深度学习的核心基础知识，在深入浅出地剖析原理的同时给出了详细的代码实现过程。如同不是教
你如何使用武器、手机而是教你如何自己制造武器、手机，本书不是已有深度学习库的使用教程而是剖
析如何从0开发深度学习库。这种从0开始的原理与代码实现结合的方式可以使读者更好地理解深度学习
的基本原理和流行的深度学习库的设计思想。
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