Welcome to the Data-Science repository — your one-stop workspace to explore, clean, and engineer data like a pro! Whether you're solving real-world problems or practicing core ML concepts, this repo has you covered with a structured, hands-on approach to EDA 📊 and Feature Engineering 🧠.
- Get a grip on dataset distributions
- Identify trends, patterns, and anomalies
- Build intuition before modeling
- 🧱 Handling Missing Values
- ⚖️ Balancing Imbalanced Datasets (with SMOTE!)
- 🔍 Detecting and Treating Outliers
- 🧠 Categorical Encoding:
- One-Hot Encoding (OHE)
- Label & Ordinal Encoding
- Target-Guided Encoding
| Notebook | Description |
|---|---|
EDA-And-FE-Flight-Price.ipynb |
Dive into the pricing secrets of flights. |
EDA-And-FE-Google-Playstore.ipynb |
Explore app data and features that win users. 📱 |
EDA-And-FE-Wine-Quality.ipynb |
Sip on data insights behind fine wine. 🍷 |
Install dependencies via:
pip install -r requirements.txt🙌 Thanks for stopping by! Whether you're learning, building, or exploring — keep experimenting, stay curious, and let the data guide you.
⭐ If you found this repo helpful, consider giving it a star and sharing it with fellow data enthusiasts!
😊 Happy Learning & Happy Coding!