This repository contains notebooks for analyzing and drawing conclusions using advanced techniques in data science, statistics, and machine learning. The following case studies are included:
- EDA with Spotify
- House Prediction Case Study
- House Price Melbourne
- IBM HR Analytics Employee Attrition & Performance Case Study
- The Complete Pokemon
- The Personality Analysis
This case study focuses on exploratory data analysis using Spotify's music data. The notebook explores various features of the songs and draws insights from the data.
This case study is based on a machine learning project to predict house prices. The notebook explores the dataset, performs feature engineering, and builds a model to predict house prices.
This case study is another machine learning project to predict house prices, this time for Melbourne. The notebook explores the data, performs data cleaning and feature engineering, and builds a model to predict house prices.
This case study explores HR analytics and focuses on employee attrition and performance. The notebook analyzes various factors that affect employee retention and performance and draws insights from the data.
This case study is based on analyzing data related to the popular game franchise, Pokemon. The notebook explores the different aspects of the Pokemon universe and provides insights into various features.
This case study focuses on analyzing personality traits using data science techniques. The notebook explores different datasets and methods to analyze and predict personality traits.