Deep Learning Framework From Scratch Using Numpy

• URL: http://arxiv.org/abs/2011.08461v1
• Date: Tue, 17 Nov 2020 06:28:05 GMT
• Title: Deep Learning Framework From Scratch Using Numpy
• Authors: Andrei Nicolae
• Abstract summary: 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 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.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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