This work is a rigorous development of a complete and general-purpose deep learning framework from the ground up. The fundamental components of deep learning - automatic differentiation and gradient methods of optimizing multivariable scalar functions - are developed from elementary calculus and implemented in a sensible object-oriented approach using only Python and the Numpy library. Demonstrations of solved problems using the framework, named ArrayFlow, include a computer vision classification task, solving for the shape of a catenary, and a 2nd order differential equation.

中文翻译：

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使用 Numpy 从头开始​​的深度学习框架

这项工作是从头开始严格开发一个完整的通用深度学习框架。深度学习的基本组成部分——优化多变量标量函数的自动微分和梯度方法——是从初等微积分发展而来的，并以合理的面向对象方法实现，仅使用 Python 和 Numpy 库。使用名为 ArrayFlow 的框架解决问题的演示包括计算机视觉分类任务、悬链线形状求解和二阶微分方程。