A curated hub for exploring the world of Artificial Intelligence, Machine Learning, and Deep Learning 🚀
Summary • Core Topics • Papers • Tables • Projects • Repo Structure • Resources
AI is transforming industries 🌍 — from healthcare and finance to autonomous systems and creative arts.
This repository serves as a knowledge hub that is:
- 📚 Educational — Learn both fundamentals and cutting-edge concepts
- 🧩 Practical — Dive into projects with real-world impact
- 🗂 Organized — Access structured comparisons & resources instantly
- 🌟 Collaborative — Open-source, welcoming contributions from the AI community
- Artificial Intelligence (AI) — Agents, reasoning, search, expert systems
- Machine Learning (ML) — Regression, classification, clustering, model evaluation
- Deep Learning (DL) — CNNs, RNNs, Transformers, GANs, LLMs
- Breakthrough Research — Landmark papers shaping the AI revolution
- MLOps & Deployment — Serving models at scale with monitoring
- Comparisons — Conceptual & technical tables for quick reference
- Projects — End-to-end, hands-on implementations
A collection of landmark research papers that shaped modern AI:
- 🧠 Perceptrons (1969) — Early neural network foundations
- 🖼 ImageNet (2009) — Deep learning’s breakthrough in computer vision
- 🎤 Attention Is All You Need (2017) — The birth of Transformers
- 📝 BERT (2018) — NLP revolution with bidirectional Transformers
- 💬 GPT Series (2018–2023) — Large language models reshaping AI
- 🧬 AlphaFold (2020) — Solving protein folding with AI
✨ More Influential Papers
- 🎨 GANs (2014) — Generative Adversarial Networks
- 🧠 ResNet (2015) — Deep residual learning
- 🗣 WaveNet (2016) — Deep learning for audio generation
Easily compare concepts, metrics, and models at a glance 👇
| Aspect | Machine Learning | Deep Learning | Generative AI |
|---|---|---|---|
| Data Needs | Small datasets | Large labeled datasets | Massive datasets |
| Interpretability | Easy to explain | Black-box models | Very complex |
| Hardware | CPU often enough | GPU/TPU required | High-performance GPUs/TPUs |
| Applications | Predictive analytics, clustering | Vision, NLP, speech | Text, image, audio generation |
✅ Find full tables in the /tables/ directory.
Hands-on projects to bridge theory → practice:
- 🔍 ML Models — Regression, classification, clustering
- 👁 Computer Vision — Object detection & defect detection (YOLOv8)
- 📝 NLP — Summarization, Q&A with Transformers
- 🎨 Generative AI — LLM fine-tuning & diffusion models
- 🛠 MLOps — Pipelines, monitoring, deployment strategies
Each project includes:
✔️ Well-documented Jupyter Notebooks
✔️ Guides & tutorials
✔️ Sample datasets or links