antoniodagnino

Oil-Gas-Drilling-Activity-Prediction

Drilling Activity Prediction: Oil and Gas operations are dramatically affected by supply, demand and several other factors that compromise the operational planning of resources. To overcome this challenge, predictive analytics could be applied to forecast rotary rig count inside United States using time-series data.

GeothermalDatathon

The U.S Department of Energy is developing Enhanced Geothermal Systems as a solution for renewable energies. The Utah Forge Project is currently searching for the optimum well placement of a production well that enables the maximum possible net energy for 20 years. ‘GeotherML’ team participated in this challenge, analyzed data provided by SPE - PIVOT, and delivered a solution that includes the use of Deep Learning. The development of this initiative covers Exploratory Data Analysis with feature engineering, data modeling and evaluation metrics.

TimeSeriesForecasting_CarbonEmissions

Forecast Carbon Emissions with Time-Series data. This repository contains 2x Jupyter Notebooks that predict Carbon Emissions in the United States using Neural Basis Expansion Analysis for Time series (NBeats). The second notebook has an extra pre-processing step of data been scaled and inverse-transformed before final results.

antoniodagnino

HOD

The dragon battle simulator explains and implements basic data analytics methods like Normalization and apply weights to attributes using Python before showing the results through Power BI reports.

PythonTraining

This repository contains Jupyter notebooks with comment lines, comment cells and outputs that explain the functionality of different libraries in Python. These 'cheat sheets' include basic Python programming, Numpy, Pandas, Matplotlib, Seaborn and more. I hope it guides you to start your programming experience! Below you have more details of the content.

RTraining

This repository contains R markdown codes with comment lines, comment cells and outputs that explain the use of different R built-in methods like vectors, matrices, dataframes, probability functions, loops, and libraries like Dplyr, tidyr, ggplot and more. I hope it guides you to start your programming experience! Below you have more details of the content.