Manu Romo @ Github

Data Wrangling Challenge in Excel: Salary Survey 2021

Summary

This is a challenge I took part in. I handled an eccentric Excel Salary Survey dataset, transforming complex characters and data into usable information. I cleaned up and organized the information, using different tools to find patterns. This challenge provided an opportunity to test my efficiency working in Excel. In this post, I will describe my process.”

Simple Naive-Bayes Implementation

Summary

This is an implementation for a simple naive bayes algorithm, a probabilistic classification algorithm based on Bayes’ theorem, which assumes that the features used to describe an observation are conditionally independent, given the class label. Despite its “naive” assumption of independence, it often performs well in practice, especially for text classification tasks. It is then applied to a dataset that deals with adults profiles and their income.

Self Research: SEO Dunkin

Description

In this exploration exercise, I analyzed a dataset sourced from Dunkin’s Marketing Department, comprising 10,000 keywords extracted from SEMrush, overseen by Meagan Voulo. The dataset consists on the following columns:

Regression Excercises (StatsModels and Scikit-Learn)

Basic exercises on regression using two Python modules: StatsModels and Scikit-Learn.

Notes and Tutorials

These are a few notes I did by solving a few exercises. At the moment there are 4 of them: EDA, ETL, Pandas and Visualization. A brief description of each is given below.