SciKit Learn Machine Learning Cheat Sheet

Code snippet to produce organized directory of scatterplots ranked by correlation coefficient

Kaggle's 'Bike Sharing Demand' competition

Python data analysis toolbox - contains practical data munging, data cleaning, data exploration examples, as well as useful data processing algorithms.

data exploratory analysis of TED talks databases. extract interesting findings from data which contains general information of each talk such as genre, broadcast rating etc and related transcripts as well.

Machine Learning Nano-degree Project : To identify customer segments hidden in product spending data collected for customers of a wholesale distributor

Data exploration of an Open Baltimore data set.

Classifying observed objects from the Kepler mission with scikit-learn.

This project is part of Udacity nanodegree program for data analysis and the project is an analysis of more than 100k medical appointments in Brazil and is focused on answering the question: Which factors if any are important in order to predict if a patient will show up for their scheduled appointment?

Portfolio Project: Data Exploration in SQL.

The app is about FIFA Data Exploration and Insights Generation. I chose this project because I am more familiar with data exploration, and It felt interesting. The project is beneficial for football analysts to provide deep analysis of football players, their abilities, expenses, and their skills/experiences. This will help teams to select right…

An analysis for the highest paid athletes for a 10 year span in Python. The data set is from the Forbes list that compiled their net worth.

This project aims to analyze the telecom market, focusing on customer demographics and their preferences for multiple telecom services. The goal is to identify age groups that are most likely to have multiple telecom services and understand their sentiment regarding the number of options they have.

Lab sessions of the Machine Learning course of the Artificial Intelligence Master's degree at UniBo

The main objective of this project is to design and implement a robust data preprocessing system that addresses common challenges such as missing values, outliers, inconsistent formatting, and noise. By performing effective data preprocessing, the project aims to enhance the quality, reliability, and usefulness of the data for machine learning.

Practice project to have good command on SQL

Implementation of Exploratory Data Analysis on Supermarket Sales Data with MySQL Workbench

The data extraction and processing involved thorough exploration, preprocessing, and visualization of the "Video Game Sales with Ratings" dataset.