D

data science

This project focuses on extracting and visualizing stock data using Python libraries such as yfinance for historical stock prices and web scraping techniques to gather company revenue data. It provides a comprehensive analysis by plotting both stock prices and revenues over time for companies like Tesla and GameStop.

Faire des analyses descriptives sur sur une base de donnée conséquente en résumer les grandes lignes

In this project, you will be provided with a real-world dataset, and you are required to implement the whole pipeline of building the data science pipeline on-premises and on-the-cloud. This includes understanding the business problem, preparing data, exploring the data, performing feature engineering, and building and deploying models

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.

Measurement data aggregator based on InfluxDB with SiLA interface. An important application is fast time series data aggregation, like data originating from sensors (temperature, pressure, pH, ...). An interface to the LARAsuite databases will be provided.

A library of blog posts and tutorials. Part of the End-to-End Machine Learning School at e2eml.school/courses

Curiously enough, the only thing that went through the mind of the bowl of petunias as it fell was Oh no, not again.

Este proyecto es material de la materia Laboratorio de Datos del Instituto de Cálculo de la Facultad de Ciencias Exactas y Naturales de la Universidad de Buenos Aries. Icon by Flaticons

En este trabajo se varían distintos hiperparámetros de una CNN para mejorar la clasificación multiclase de imágenes

Evaluación de distintos modelos para clasificar aguas entre potables y no potables

Search for patterns in river water samples data

Calculation of covariance of cosmological maps in the BINGO radio telescope pipeline.

[Python] Step-by-step Data Science project in accordance with Data Science pipeline in practice to build a predictive model for average salary of job listings

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

Vamos a contruir un Chatbot Inteligente capaz de interpretar el lenguaje humano y generar respuestas coherentes con tu propia información

A collection of Data Science projects.

La junta directiva de la cadena de supermercados Universal Food ha observado una estabilización en sus ventas y busca comprender cómo mejorar la relación con sus clientes, entendiendo sus hábitos de compra, para ofrecerles un servicio de mayor calidad. El objetivo es proporcionarles una experiencia de compra más personalizada, rápida y efectiva.

This project I created to show how to develop a docker image to use for data science applications

This project contains the source files I used in a free-lance project for a book reseller.

Python environment setup SQL (mariadb) database configuration setup of a Python-mariadb connector Data enrichment with the seller's local currency value in time. Data analysis with Python [pandas, scikit-learn, matplotlib, seaborn] Brief interpretation of the data is present in the notebook.