Data Science Bootcamp Project

This repository contains the code and materials for my Data Science Bootcamp on qwasar projects.

Overview

This project is the culmination of my journey through the Data Science Bootcamp. It demonstrates the application of key concepts and skills learned during the bootcamp.

Key Concepts

• Data Exploration: Explored and analyzed various datasets to understand their characteristics.
• Statistical Analysis: Applied statistical techniques to derive insights from data.
• Machine Learning: Developed and trained machine learning models for predictive tasks.
• Data Visualization: Created informative visualizations using tools such as Matplotlib and Seaborn.
• Data Cleaning: Performed data cleaning and preprocessing to ensure data quality.
• Feature Engineering: Engineered new features to improve model performance.
• Model Evaluation: Evaluated model performance using appropriate metrics.

Tools and Technologies

• Programming Language: Python, java, c
• Libraries and Frameworks: NumPy, Pandas, Scikit-Learn, Matplotlib, Seaborn
• Machine Learning Framework: scikit- learn
• Data Analysis: Jupyter Notebooks