This repository contains some exciting and novel ML projects.
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Draw_Choropleth_Maps: In this project, we work with Choropleth maps to estimate the population of the Northeast Region of Brazil.
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Gender_UFRN_Employess: In this project, we identify the gender of each employee and visualize the gender gap using a pie graph. Also, we find the first female and male names more commons among UFRN employees.
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Montgomery_County_Crime_Analisys: In this project, you'll be working with crime data from Montgomery County, MD. Each row in the data is a crime reported by a law enforcement officer in 2013 and entered into a database.
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UBER_Estimated_Times_Analysis: In this example, the analysis of the average time it takes for a UBER car to arrive at a specific point (latitude, longitude) within a neighborhood is made. The study has been carried out in the city of Natal. This metropolis belongs to the state of Rio Grande do Norte in Brazil. Data were obtained during eight days, for 3 points within each neighborhood (36 in total) of Natal. The data capture period was four minutes because the UBER API only allows 2000 queries per hour.
For this example it is necessary:
- Jupyter-Notebook
- [Pandas](!pip install pandas)
Download the files and run using Jupyter.
If you find any of these codes helpful, please share my GitHub and STAR⭐this repository to help other enthusiasts to find these tools. Remember, the knowledge must be shared. Otherwise, it is useless and lost in time.
This project is licensed under the MIT License - see the LICENSE.md file for details.