S

seaborn

Taken from https://dev.to/oscarleo/how-to-create-a-beautiful-polar-histogram-with-python-and-matplotlib-400l

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.

This project shows an example of how a collaborative collected FAIR dataset can be extended (using Merge Requests), curated (using automated testing), analyzed (using a Snakemake workflow), and visualized (using Python).

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.

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.

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

Code from mechanic physics labs (university course)

My attempts to solve homework from the Moscow Institute of Physics and Technology course

All left code from labs 1-3 years(university studing)

Collection of completed data-mining (university course) on python

Final project of course ML junior by Skillbox. Goal: Build model to predict client's loan default. Metrics: ROC-AUC

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.

Работа с базой данных PostgreSQL и длинными запросами

Финальная работа по курсу Введение в DS от Skillbox. Цель: анализ данных сервиса СберАвтоподписка, предсказание совершения целевого действия пользователя и подготовка модели к деплою в продакшн. Метрика: ROC-AUC

Trabajas como científico/a de datos para Data Insider, un reconocido equipo de asesores financieros con presencia global, y te ha sido solicitado que elabores un informe detallado para entender de manera objetiva el comportamiento de grandes corporaciones a nivel mundial a partir del año 2015.

This jupyter notebook goes through how to use python in you data analysis. Mainly analysis of experiments, such as peak analysis and curve fitting.

This is a Collaborative-Based Movie Recommendation System developed using methods of weighted_average and Normalization(MinMaxScaling()) of Average Rating and Popularity values.

A Jupyter notebook for analysis of corona cases