Eolaí sonraí · Mandáil spóirt · Valencia

Tiontaím sonraí go cinntí soiléir

Is mise an droichead idir anailís sonraí agus spóirt mionlaigh: athraím méadrachtaí feidhmíochta ina straitéisí a dhéanann an difreáil ar an talamh.

Féach ar thionscadail Teagmháil

Python
R
SQL
Power BI
Machine Learning

Fúm

Sonraí le comhthéacs rianta, bóthair agus comórtais

Is mise Mario Álvarez, mac léinn Eolaíochta Sonraí san UPV le taithí réadúil laistigh de rothaíocht ghairmiúil. Comhcheanglaím anailís sonraí le feidhmíocht spóirt mhionlaigh, chun gach méadracht a thiontú ina chinneadh a fheabhsaíonn torthaí.

Féach tuilleadh

UPV

Oideachas

Céim san Eolaíocht Sonraí, Universitat Politècnica de València.

Mionlach

Taithí

Obair réadúil laistigh d'fhoireann rothaíochta ghairstiúil.

Data + Sport

Cur chuige

Anailís a cuireadh i bhfeidhm chun feidhmíocht spóirt a fheabhsú.

Taithí

Dhá domhan, teanga amháin: an fheidhmíocht

Bhí mé san iomaíocht ag an leibhéal is airde agus inniu cuirim an critéar céanna i bhfeidhm ar na sonraí: tuigim cad a chiallaíonn uimhir do spóirtseach toisc gurbh mise an spóirtseach sin.

Féach tuilleadh

Obair

Tionscadail

Roghnú uathoibríoch de mo stórtha poiblí ar GitHub.

Speisialtachtaí

HTML
Power BI
Python
R
SQL

VIS

HTML

This repository contains coursework, practical exercises, and study materials for a university data visualization course. It includes solved programming tasks using R and Python libraries like ggplot2 and Plotly, alongside practice dashboards built in Tableau.

Féach ar GitHub

EVALUACION-DE-MODELOS-

HTML

This repository contains practical assignments for a university model evaluation course, covering topics such as cost-sensitive classification, fairness metrics on the COMPAS dataset, and model interpretability using partial dependence plots. The exercises and analyses are implemented using Python and R across Jupyter Notebooks and R Markdown reports.

Féach ar GitHub

TRABAJO_MDP

An academic data analysis project in R that explores and characterizes a physicochemical crystal dataset. It covers data cleaning, preprocessing, and dimensionality reduction through Principal Component Analysis (PCA) using packages such as FactoMineR, factoextra, and ggplot2.

Féach ar GitHub

TRABAJO_CORREDORES

Python

A Streamlit web application that helps manage cycling teams by scraping race and rider data from ProCyclingStats and FirstCycling to analyze upcoming events and cyclist specialties. It is built with Python using BeautifulSoup, Selenium, Pandas, and the Gemini API to process data and extract UCI points regulations from PDFs.

Féach ar GitHub

COFIDIS

Python

Developed as an academic project, this tool scrapes UCI rankings and race data from ProCyclingStats to calculate race difficulty scores tailored to the Cofidis cycling team's calendar. It is built with Python, using Selenium and BeautifulSoup for web scraping, Pandas for data processing, and Streamlit for the interactive interface.

Féach ar GitHub