Welcome to my Data Science Learning Repository — a collection of my notes, experiments, and projects as I dive deep into the world of Data Science and Machine Learning.
Each folder in this repo represents a key milestone — from understanding data to building real-world AI models.
| Folder | Description |
|---|---|
📂 datacollecting |
Techniques for collecting and cleaning data from different sources (APIs, web scraping, CSVs). |
📂 numpy |
My hands-on practice with NumPy — arrays, broadcasting, indexing, and linear algebra operations. |
📂 pandas |
Data manipulation, cleaning, merging, and analysis using Pandas. |
📂 matplotlib |
Data visualization basics — plotting, styling, and customizing charts. |
📂 seaborn |
Advanced visualizations and statistical plots for deeper EDA. |
📂 probabilityfords |
Probability, statistics, and math concepts for understanding ML fundamentals. |
📂 sk-learn |
Machine learning models: regression, classification, clustering, pipelines, and evaluation. |
📂 deep learning |
Experiments with neural networks, TensorFlow/Keras, and model optimization. |
- Languages: Python 🐍
- Libraries: NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, TensorFlow
- Visualization: Matplotlib, Seaborn
- Data Handling: Pandas, NumPy
- ML Frameworks: Scikit-learn, TensorFlow
- Others: Jupyter Notebook, VS Code
To document my progress as I transition from learning Data Science fundamentals
to mastering Machine Learning, Deep Learning, and AI systems.
This repo acts as both:
- My personal learning log 📓
- And a portfolio reference 💼 for others learning Data Science
✅ Data Collection & Cleaning
✅ Exploratory Data Analysis (EDA)
✅ Probability & Statistics
✅ Machine Learning Algorithms
✅ Deep Learning Basics
- Advanced Deep Learning (CNNs, RNNs)
- NLP & Large Language Models
- MLOps & Deployment
- AI Project Case Studies
“To master Data Science and Machine Learning end-to-end —
from understanding data to building intelligent, deployable systems.”
📬 GitHub: @SonuSwain526
💼 LinkedIn: [Your LinkedIn URL here]
🐦 Twitter (optional): [Your Twitter if available]
⭐ If you find this repo helpful, consider giving it a star!
It motivates me to learn, share, and grow even faster 🌟