Solve classic mechanics problems with python, Solve problems of Static, Dynamics, Work, Energy, Kinematics, with Atb python library

Automatic code generation of Fast Multipole and Barnes-Hut operators

my python mini projects as part of the complete python Pro Bootcamp for 2023 - 100 Days of Code course

1D shimming coil design and optimisation algorithm

LaTeX Matrix Calculator. Paste your matrix latex code and view/copy the results.

SymPy is a Python library for symbolic mathematics

Simulations of various concepts of Control Systems Engineering using python and google colab. Developed by students of BMS College of Engineering, Bengaluru.

A SymPy module for Modified Nodal Analysis

This is my Coursera courses notebook

All data and analyses to reproduce my ice material science research, as published in Penn Science: Furman and Goldsby, 2021.

Multimodal, intelligent LLM and RAG-powered math tutor capable of combining the power of NLP with CAS to produce answers that are mathematically-sound, hallucination-free, and easy to digest with step-by-step solutions delivered using natural language. Support LaTeX front-end rendering with libraries such as MathJax

A shell for handling SymPy matrix objects

Mean field variational Gaussian process algorithm. This repository contains a python3 implementation of the variational mean field algorithm as described in the paper: Physical Review E. vol. 91, 2015, 012148.

Pinta los pixeles primos en imagen, leer el comentario principal del código fuente para saber como hacerlo funcionar

[PyPi Package] - performs integral and differentiable operations on string expressions using sympy

🎭 Storyteling for Data Science and Artificial Intelligence - PUC-SP University

Learn Python Programming

Calc-Ultra is a calculus calculator. Supports calculus and linear algebra calculations!

The focus of function approximation problems has been on identifying some suitable function without attempting to gain insight into the mechanism of the system. The performance of the model boils down to interpolation. But, in a more realistic setting, we expect test data from outside the distribution of the training set. To better extrapolate t…