NumPy

MCODAC is a Fortran library for the numerical evaluation of fiber composite damage. The library contains analysis methods specifically tailored to fiber composites, from micromechanical homogenization approaches to macroscopic fatigue models of orthotropic multilayer composites.

dantro is a python package for handling, transforming, and visualizing hierarchically organized data.

Integrated into data-intensive projects, it supplies an easy way to define a customizable, configuration-based data processing pipeline. See utopya for an example.

Boxbeam is a legacy Fortran tool translated to python. It calculates effective beam properties of composite cross sections comprised of rod-like elements.

Beos is a legacy Fortran tool used to calculate the static and dynamic buckling behavior of flat/curved fiber composite structures.

API construída em Python para realizar reconhecimento facial de uma imagem e comparar com outras imagens armazenadas em um banco de dados Mongodb, e retornar se é a mesma pessoa. Serviços do projeto foram feitos em docker com containers para a api e o mongo.

This project predicts house prices using machine learning models based on the King County House Sales dataset. It explores Simple Linear, Multiple Linear, Polynomial, and Ridge Regression models, comparing their performance in terms of accuracy. The best model identified is Polynomial Regression, achieving an R² score of 0.75.

Common statistics and functions to work with financial time series.

A pricing graph of the 930, 964, and 993 generations of Porsche 911s based on data from Cars & Bids.

Lecture note of Numerical Analysis and Practice

A project to develop a non-invasive, AI-powered system for detecting lung cancer associated with combustion particles and fine particulate matter (PM2.5).

В данном репозитории находятся два проекта, демонстрирующие работу c данными в Python и на SQL, а также использование специализированных библиотек для статистических расчетов и визуализации данных, в Jupiter Notebook.

Introduction to classification using machine learning and deep learning (PyTorch, TensorFlow, Keras)

Various examples of some data analysis exercises.

Este repositorio contiene los dos casos de estudio realizados como parte del Diplomado de Extensión en Data Science. En ambos casos, se utilizaron técnicas de programación en Python y Data Science para analizar conjuntos de datos y extraer información valiosa.

A Python module, primarily on linear and multiple regression including normalizing data, computing hypothesis, and evaluating cost.

A project focused on weather classification using advanced deep learning techniques, specifically leveraging TensorFlow and a custom Convolutional Neural Network (CNN). The project involved the integration of four diverse weather datasets, namely ACDC, MWD, UAVid, and Syndrone, covering various weather conditions, including clear sky, cloudy, rainy, and sunny weather. Developed a custom CNN architecture using TensorFlow's Keras API, incorporating convolutional layers for feature extraction and dense layers for classification.

Basic numpy usage

This Car Prediction Project aims to predict v price, using Regression models. The project contains a collection of data files, model files, and Python scripts necessary for training and deploying car prediction Price models. This project encompasses a comprehensive set of data files, serialized models, and Python scripts necessary for training, evaluating, and deploying car price prediction models.

Creation of a trading robot for data analysis and manipulation of the libraries Pandas, Numby, MatplotLib, Yfinance, Seaborn