Data Science Jupyter Notebooks
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Explore the world of Data Science through Jupyter Notebooksβ€”insights, tutorials, and tools to boost your data journey. Code, analyze, and visualize smarter with every post.
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πŸ“Œ The official GitHub repository for the book
Hands-On Machine Learning (2nd Edition)

πŸ“” Contains Jupyter notebooks covering:
βšͺ️Machine Learning Principles (Linear Models, Decision Trees, SVM).
βšͺ️Unsupervised Algorithms (Clustering, PCA).
βšͺ️Advanced Neural Networks (ANN, CNN, RNN, LSTM).
βšͺ️How Transformers Work.
βšͺ️Reinforcement Learning.
βšͺ️Building and Training Models with TensorFlow 2 & Keras.
βšͺ️Deploying and Scaling Models to Production Environments.
βšͺ️Data Science Tools (Pandas, NumPy, Matplotlib, Scikit-Learn).
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1️⃣ Data Science
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Top 50 LLM Interview Questions!

A comprehensive resource that covers traditional ML basics, model architectures, real-world case studies, and theoretical foundations.

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10 GitHub repos to build a career in AI engineering:

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1️⃣ ML for Beginners by Microsoft

A 12-week project-based curriculum that teaches classical ML using Scikit-learn on real-world datasets.

Includes quizzes, lessons, and hands-on projects, with some videos.

GitHub repo β†’ https://lnkd.in/dCxStbYv

2️⃣ AI for Beginners by Microsoft

This repo covers neural networks, NLP, CV, transformers, ethics & more. There are hands-on labs in PyTorch & TensorFlow using Jupyter.

Beginner-friendly, project-based, and full of real-world apps.

GitHub repo β†’ https://lnkd.in/dwS5Jk9E

3️⃣ Neural Networks: Zero to Hero

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This repo by Andrej Karpathy builds modern deep learning systems from scratch, including GPTs.

GitHub repo β†’ https://lnkd.in/dXAQWucq

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So far, you have learned the fundamentals of AI, ML, and DL. Now study how the best architectures work.

This repo covers well-documented PyTorch implementations of 60+ research papers on Transformers, GANs, Diffusion models, etc.

GitHub repo β†’ https://lnkd.in/dTrtDrvs

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Now it’s time to learn how to go from notebooks to production.

Made With ML teaches you how to design, develop, deploy, and iterate on real-world ML systems using MLOps, CI/CD, and best practices.

GitHub repo β†’ https://lnkd.in/dYyjjBGb

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Now apply them. This is a visually rich repo that covers everything about LLMs, like tokenization, fine-tuning, RAG, etc.

GitHub repo β†’ https://lnkd.in/dh2FwYFe

7️⃣ Advanced RAG Techniques

Hands-on LLMs will give you a good grasp of RAG systems. Now learn advanced RAG techniques.

This repo covers 30+ methods to make RAG systems faster, smarter, and accurate, like HyDE, GraphRAG, etc.

GitHub repo β†’ https://lnkd.in/dBKxtX-D

8️⃣ AI Agents for Beginners by Microsoft

After diving into LLMs and mastering RAG, learn how to build AI agents.

This hands-on course covers building AI agents using frameworks like AutoGen.

GitHub repo β†’ https://lnkd.in/dbFeuznE

9️⃣ Agents Towards Production

The above course will teach what AI agents are. Next, learn how to ship them.

This is a practical playbook for building agents covering memory, orchestration, deployment, security & more.

GitHub repo β†’ https://lnkd.in/dcwmamSb

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To truly master LLMs, RAG, and AI agents, you need projects.

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Gemini CLI

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