Kaggle Practice Projects

A set of exploratory data analysis and machine learning notebooks built as practice projects using Kaggle datasets. Covers real estate pricing, wine review sentiment, and market basket analysis.

---

📁 Repository Structure

File	Dataset	Focus Area
Project_Home.ipynb	Home Prices (1mgData.csv)	EDA, Regression
Wine_Enthusiasts.ipynb	Wine Reviews	EDA, Sentiment / Rating Analysis
market-analysis.ipynb	Market Data	Market Basket / Association Analysis

---

📊 Project Summaries

Project 1 — Home Prices

Explores real estate data to understand what factors drive property prices. Performs EDA and builds predictive regression models to estimate home valuations.

Project 2 — Wine Enthusiasts

Analyzes a Kaggle wine reviews dataset to understand patterns in critic ratings, wine varieties, countries, and price.

Project 3 — Market Analysis

Applies market analysis techniques to identify patterns in product purchasing behavior.

---

🛠️ Technologies & Libraries

• Python 3.x, Jupyter Notebook
• pandas, numpy, matplotlib, seaborn, scikit-learn

---

🚀 Getting Started

1. Clone the repository:

   git clone https://github.com/janmejoykar1807/KagglePracticeProject.git

2. Install dependencies:

   pip install pandas numpy scikit-learn matplotlib seaborn jupyter

3. Open any .ipynb file in Jupyter Notebook.

---

👤 Author

Janmejoy Kar Data Science learner — applying Python, R, and SQL for data analysis and predictive modeling. GitHub Profile