Statistics and Queries on Pyspark
Creating Plotly Visualizations and Probability Distribution with PyMC4 using PySpark for extracting data.
A little about me
I am a data scientist with research experience. I enjoy digging into any kind of data, extracting as much as possible from them using an analytical and statistical approach along with amazing visualizations including dashboards, dynamic charts and Web Mapping. I have worked with really different data, from financial data to climatology output models data and satellite products, so I am used to learning new tools every day.
Some Projects
F1 Ultimate Data Analysis App
Telemetry, driving styles, strategies, weather, track conditions and more data analysis using official F1 data displayed in a web app that is automatically updated after every race weekend.
Predicting Rain on Australia
Full EDA, Feature Selection techniques and machine learning modelling for rain prediction.
Predicting whether a customer would answer a phone call
Machine Learning model design based on call history and demographic data from customers.
Global Warming on the Last Millenium
Dashboard of temperature changes in the world from 850 to 2005 a.c. with data output from the Community Earth System Model and the Last Millennium Ensemble Project.
Web Mapping for Extreme Dust Storm in Urban area
Web Map from WRF-CHEM model simulation output data using Folium, Netcdf4, geopandas and more.
Products Sales Forecasting
Full EDA, Feature Selection and machine learning modelling for Products Sales Forecasting.
A/B Testing for gaming industry
Data Exploration, Probability of player retention analysis and A/B testing with python.
Songs genre classification
Principal Component Analysis, Feature Engineering, Machine Learning modelling and the recipe for composing a popular song based in data insights.