quantsci

quantitative methods for science and engineering

This is a work in progress. The content is not final and may change. If you have any suggestions, please send us a message in contact@quantsci.org

Materials

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Optimization in Deep Learning and Engineering

ODLE is a optimization book for deep learning and engineering with applications in Python

Graphnet

graphnet is an open repository for graphs and machine learning on graphs.

Responsible AI

Responsible AI: Theory and Practice aims to present the key concepts in one of the most important areas for technological development in the 21st century.

Causal Inference in Machine Learning

This is a comprehensive guide to causal inference in machine learning.

Modern Time Series Analysis and Forecasting

This is a comprehensive guide to moder approach for time series analysis and forecasting.

Open-Source Code and Tools

Select a resource below to learn more about it.

optymus

The main goal is provide a simple structure to improve research and development in optimization problems.

compute-geometry

A comprehensive computational geometry library for Python. This library is designed to provide a set of tools and algorithms for solving geometric problems.

Machine Learning 101

This is a repository with the basics of machine learning, including the most important algorithms and concepts.

Deep Learning 101

This is a repository with the basics of deep learning, including the most important algorithms and concepts.

Cite this project as:

@misc{quantsci2024,
    author = {Costa, K., Modenesi, B., Tsallis, E., Gallas, J., Caetano, I., Spyrides., G., Miranda., C.},
    title = {Quantitative methods for science and engineering},
    year = {2024},
    url = {https://quantsci.org}
    }

Introduction