This repository documents my 21-day hands-on journey through Machine Learning, Deep Learning, and Generative AI, where I build one real-world project each day.
It serves as a single, organized place to track my learning, experiments, and end-to-end AI projects — all pushed consistently as I progress.
- Machine Learning projects covering prediction, classification, and segmentation tasks
- Deep Learning implementations using CNNs, transfer learning, and time-series models
- Generative AI applications such as OCR systems, Text-to-SQL models, RAG-based chatbots, and AI agents
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Projects are grouped week-wise by focus area:
- Week 1: Machine Learning
- Week 2: Deep Learning
- Week 3: Generative AI & Agentic AI
- To build consistency through daily project-based learning
- To apply concepts to practical, real-world problems
- To maintain a clean, transparent public record of my AI/ML growth
- Programming Language: Python
- Data Analysis: NumPy, Pandas, Matplotlib, Seaborn
- Machine Learning: Scikit-learn
- Deep Learning: TensorFlow / PyTorch, Keras
- Computer Vision: OpenCV, CNNs, Transfer Learning
- Generative AI & NLP: Hugging Face, Transformers, LangChain
- AI Systems: RAG pipelines, Text-to-SQL, OCR, AI Agents
- Development: Jupyter Notebook, VS Code, Git