NumPy

This repo will have all resources, labs, data which I use/d on Kaggle Network

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.

🤖🚛Supercharge logistics with GCP ADK agent & Gemini on Cloud Run. It has multimodal chat, manages the fleet, tracks inventory, and uses tools for live data. All interactions are logged to BigQuery for instant insights.

Provides fractional delay filter design and evaluation routines for Numpy arrays

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.

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

Lecture note of Numerical Analysis and Practice

This project is a simple implementation of a neuron using Python. It demonstrates the basic concepts of a neuron, including weights, bias, and activation functions.

A data science project focused on analyzing a car market dataset from Turkey in 2020. The goal is to explore the data, apply various analytical techniques, and derive insights. The specific direction of analysis will be determined through exploration, with potential for building predictive models or visualizing trends in the market.

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

The python-native Latina Conservatory version of the SMS (Spectral Modeling Synthesis) tools developed by Xavier Serra in his Phd thesis in 1989.

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

Training various machine learning models for NFLX stock price prediction with data collection, cleaning, and visualization tools.

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.

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.

Various examples of some data analysis exercises.