bellabeat-eda

This is my first personal project, I take the Data Analytics certification by Google and as final project I made this project in where I did an EDA for Bellabeat and the data come from Kaggle.

cookiecutter-personal

covid_analysis

curso-entorno-avanzado-ds

datasets-platzi-course

Datos para los distintos notebooks del curso de platzi

deep-learning-platzi

Materiales del curso de Deep Learning con Pytorch de Platzi

graph_zfactor

In this project, it is generate a graph depicting the gas compressibility factor (z), aiming to replicate the z plot presented in (Craft & Howkins, 1991).This involves employing the Dranchuk and Abou-Kassem correlation and implementing the secant method for accurate results.

hands-on-data-analysis-with-pandas-2nd-edition

Materials for following along with Hands-On Data Analysis with Pandas – Second Edition

hands-on-exploratory-data-analysis-with-python

Hands-on Exploratory Data Analysis with Python, published by Packt

machine-learning-platzi

Notebooks del curso de machine learning aplicado con python de platzi

machine-learning-tsf-petroleum-production

Time series forecasting (TSF) is the task of predicting future values of a given sequence using historical data. Recently, this task has attracted the attention of researchers in the area of machine learning to address the limitations of traditional forecasting methods, which are time-consuming and full of complexity. With the increasing availability of extensive amounts of historical data along with the need of performing accurate production forecasting, particularly a powerful forecasting technique infers the stochastic dependency between past and future values is highly needed. In this research, we applied machine learning approach capable to address the limitations of traditional forecasting approaches and show accurate predictions and showed comparison of different machine learning models. For evaluation purpose, a case study from the petroleum industry domain is carried out using the production data of an actual gas field of Bangladesh. Toward a fair evaluation, the performance of the models were evaluated by measuring the goodness of fit through the coefficient of determination (R2 ) and Root Mean Square Error (RMSE), Mean Squared Error (MSE) , Mean Absolute Error(MAE) and model Accuracy

pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

pandas_exercises

Practice your pandas skills!

practical-statistics-for-data-scientists

Code repository for O'Reilly book

pressure-buildup-test-analsis

PBU test data taken from Tarek Ahmed

proyectos-ciencia-datos

Repositorio del proyecto del Curso para Crear tus Proyectos de Ciencia de Datos

pydata-book

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

pyreservoir

Python utilities for reservoir engineering calculations

reservoir-engineering-gas-propertiesr

The goal of this project is to provide a Python-based solution for calculating the properties of gas in a reservoir. As a result, this code will be a valuable resource for Petroleum Engineering students who want to learn more about the implementation and calculation of these properties.

ricardod671

ricardod671.github.io

rna-vgg16

Procesamiento de cartas dinamométricas con red neuronal convolucional VGG16

sql_book

Code repository for the book SQL for Data Analysis