elia-mercatanti/deep-learning-symbolic-mathematics
Discussion and test of the first successful approach to solving symbolic mathematics problems through the use of neural networks, proposed for the first time by two Facebook researchers, Guillaume Lample and François Charton. My Master Degree Thesis in Data Science.
This project provides an AI model that can solve complex symbolic mathematics problems, such as finding derivatives, integrals, or solutions to differential equations. You input a mathematical expression, and the model outputs its symbolic solution. This is ideal for mathematicians, physicists, engineers, or anyone working with advanced mathematical models who needs to automate or verify symbolic calculations.
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Use this if you need to automatically derive, integrate, or solve ordinary differential equations for complex mathematical expressions.
Not ideal if you are looking for numerical approximations or a basic calculator for simple arithmetic.
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Dec 09, 2021
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