(BOOK) Time to get your data sorted! The Data Preparation Handbook, published by Manning within the MEAP release, is the go-to guide for handling messy data. All the book's code and resources can be found here.

Using three supervised learning models for predicting whether a person is a potential donor for a charity organization and performing feature importance analysis to determine the most important features that impacts someone's probability of being a donor.

This repository contains a collection of labs that explore various machine learning algorithms and techniques. Each lab focuses on a specific topic and provides detailed explanations, code examples, and analysis. The labs cover clustering, classification and regression algos, hyperparameter tuning, data-preprocessing and various evaluation metrics.

Cyclistic

Repository for ML-AI projects

This repository contains the course fulfillment assignments for CSP/MATH 571 course at Illinois Tech (Fall-19).

No description provided.

Data Processing for Turkey İş Bankası ML Challenge #5 Competition.

Data Prep using Pandas & Visualization using Tableau for London Bike Shared Rides

Solving Tableau Prep challenge 2023 Week 4 using SQL/Snowflake

This Power BI dashboard presents an interactive and insightful analysis of the Titanic passenger survival rates based on various demographic and travel-related factors. The dashboard leverages the historic Titanic dataset to explore patterns in survival outcomes and uncover key insights.

Solving Tableau Prep challenge 2023 Week 2 using SQL/Snowflake

The Bike Sharing Company wants to understand the independent variables on their past data to analyze and create a machine learning model to understand the demand of the bike and accordingly plan a business strategy.

Python statistical data analysis project on stored preprocessed data, data manipulation and preparation

No description provided.

This repository focuses on building several Classification Machine Learning algorithms from scratch following the standard approach of using Data Exploration/Data Preparation techniques. Several algorithms (Logistic, XGBoost, KNN, SVC, Naive Bayes) were trained and used to predict the unseen data. All the algorithms were built as part of Analytics Vidhya Competition

Solving Tableau Prep challenge 2023 Week 3 using SQL/Snowflake

exercise meant as a way to practice SQL skills

A data analytics case study that includes R to clean, analyze and process the data, Tableau to create visualizations and Google Slides in creating a presentation

Customer satisfaction study (data preparation, hypothesis, ab tests)

Data Quality Assessment , Data Insights and Presentation

dataWave submission for the Pacific Dataviz Challenge 2025.