This repository is a personal learning hub where I collect, organize, and upload resources related to Data Science, Python Programming, Machine Learning, and Artificial Intelligence.
It includes notes, Jupyter notebooks, mini-projects, practice problems, and reference material that I’ve worked on as part of my continuous learning journey in these fields.
- 📌 Track my learning progress and practice
- 📌 Consolidate useful resources and notes
- 📌 Share my understanding with others in a structured way
- 📌 Build a strong foundation in AI/ML with Python
This repo will continue to grow over time. Topics include (but are not limited to):
- Python for Data Science (NumPy, Pandas, Matplotlib, etc.)
- Machine Learning Fundamentals (Supervised/Unsupervised Learning)
- Scikit-learn Workflows
- Exploratory Data Analysis (EDA)
- Data Cleaning and Preprocessing
- Model Evaluation and Metrics
- Deep Learning (basics coming soon...)
- Mini Projects / Practice Problems
- Interview-style ML questions
- Conceptual notes + code explanations