Welcome! 👋
This repository is my personal learning space where I document everything I learn on my journey toward becoming an AI Engineer. It contains my notes, experiments, projects, and practical implementations as I continue learning and building real-world AI solutions.
- Study Notes
- Jupyter Notebooks
- Data Analysis & Visualization
- Machine Learning
- Mathematics for AI
- SQL Notes & Practice
- Real-World Machine Learning Projects
- Model Deployment & Streamlit Apps
Inside this repository, you'll find learning resources covering:
- Python Programming
- NumPy
- Pandas
- Matplotlib
- Seaborn
- Plotly
- Machine Learning
- Mathematics
- PostgreSQL
- SQL Notes & Practice Queries
- EDA (Exploratory Data Analysis)
- Model Building & Evaluation
- Feature Engineering
- Model Deployment using Streamlit
Some of the projects currently available in this repository include:
- Student Success Predictor
- Employee Salary Predictor
- Loan Approval Predictor
- Heart Disease Predictor
- Retail Customer Segmentation
- Employee Attrition Prediction & HR Analytics System
- AI Cloud Cost Prediction
- 💳 Fraud Detection System
This repository is not a course or a tutorial.
Instead, it is a collection of my:
- Learning
- Practice
- Notes
- Experiments
- Mistakes
- Discoveries
- Projects
- Problem Solving
- Portfolio Work
- Progress Over Time
This repository will continue growing as I explore more topics, including:
- Deep Learning
- Computer Vision
- Natural Language Processing (NLP)
- Large Language Models (LLMs)
- Generative AI
- MLOps & Cloud Deployment
Thank you for visiting my repository!
Feel free to explore the notebooks, notes, SQL practice, machine learning projects, and experiments as I continue my journey toward becoming an AI Engineer.
⭐ Happy Learning!