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Top 23 Jupyter Notebook Python Projects
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Project mention: What Building Redis, Git and an LLM From Scratch Taught Us About Using Them | dev.to | 2026-10-05
RAG and agents. LLMs from scratch and Karpathy's Zero to Hero cover tokens, embeddings, attention. Chunking and retrieval choices stop being folklore.
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AppSignal
Monitoring that respects your time & budget. APM, error tracking, and dashboards for modern web apps. Ten-minute setup, transparent flat pricing, and support from engineers who actually use the product.
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A beginner-friendly ML curriculum with practical examples and exercises you can actually finish. A solid starting point if you’re new to ML and want quick wins. Link: https://github.com/microsoft/ML-For-Beginners
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The linked Github seems to have the 2nd edition in the form of notebooks, https://github.com/jakevdp/PythonDataScienceHandbook/blob/ma..., under the Using Code Examples section, "attribution usually includes the title, author, publisher, and ISBN. For example: "Python Data Science Handbook, 2nd edition, by Jake VanderPlas (O’Reilly). Copyright 2023..." compared to the OP's link which has "The Python Data Science Handbook by Jake VanderPlas (O’Reilly). Copyright 2016..."
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RAG_Techniques
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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Project mention: GSoC 2026 Predictions: 30 NEW AI/ML/Security Organizations You Should Start Contributing to NOW! | dev.to | 2026-02-06
fastai: https://github.com/fastai/fastai ⭐ 26k+
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Project mention: GSoC 2026 Predictions: 30 NEW AI/ML/Security Organizations You Should Start Contributing to NOW! | dev.to | 2026-02-06
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homemade-machine-learning
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
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GenAI_Agents
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
Clear tutorials and implementations of generative AI agent techniques, from basic builds to advanced strategies. You’ll see how different agent strategies are wired up, which makes design choices feel obvious. Link: https://github.com/NirDiamant/GenAI_Agents
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Project mention: Integer Palindromes – 2026 AIME I Problems/Problem 2 | news.ycombinator.com | 2026-09-16
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agents-towards-production
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
Project mention: Show HN: GibRAM an in-memory ephemeral GraphRAG runtime for retrieval | news.ycombinator.com | 2026-01-17GraphRAG's approach certainly makes sense for regulation-heavy documents, where interconnected references can be critical for retrieval quality. The challenge you mentioned about separate systems for graph storage and vector indexing resonates with what we've seen in the field. In practice, this separation often adds unnecessary complexity for ephemeral analysis tasks. One thing we've explored is using a dual-memory architecture, which might be relevant here even in an in-memory context. It allows you to effectively manage recent context and longer-term semantic connections without the overhead of persistent storage. If you're interested in seeing how this approach could be integrated into production systems, I wrote up some patterns that might be useful: https://github.com/NirDiamant/agents-towards-production.
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llama-cookbook
Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services
While people often focus on the big models, smaller and more specialised models are increasingly important. Codex for code generation, Stable Diffusion for images, and small LLaMA-class models for focused tasks are all good examples.
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awesome-python-applications
💿 Free software that works great, and also happens to be open-source Python.
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mcp-for-beginners
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.
MCP for Beginners (Microsoft): 13 modules on the Model Context Protocol. You build your own MCP server and client. https://github.com/microsoft/mcp-for-beginners
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vosk-api
Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
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python-machine-learning-book
The "Python Machine Learning (1st edition)" book code repository and info resource
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The-Complete-FAANG-Preparation
Dive into this repository, a comprehensive resource covering Data Structures, Algorithms, 450 DSA by Love Babbar, Striver DSA sheet, Apna College DSA Sheet, and FAANG Questions! 🚀 That's not all! We've got Technical Subjects like Operating Systems, DBMS, SQL, Computer Networks, and Object-Oriented Programming, all waiting for you.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Jupyter Notebook Python discussion
Jupyter Notebook Python related posts
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What If We Stopped Using GPUs? [video]
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Building a Large Language Model from Scratch: A Comprehensive Learning Guide
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EveryCli : a natural-language command-line assistant
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Optimizing for the 8GB Barrier: Strategic Model Selection for Local AI
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Integer Palindromes – 2026 AIME I Problems/Problem 2
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How Hard Is It to Find a Remote Python Data Job? I Checked 88,975 HN Job Posts
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Unsloth Desktop brings Local AI to the masses
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A note from our sponsor - AppSignal
www.appsignal.com | 5 Oct 2026
Index
What are some of the best open-source Python projects in Jupyter Notebook? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | LLMs-from-scratch | 105,828 |
| 2 | ML-For-Beginners | 91,244 |
| 3 | PythonDataScienceHandbook | 49,933 |
| 4 | Made-With-ML | 49,672 |
| 5 | TensorFlow-Examples | 43,739 |
| 6 | Data-Science-For-Beginners | 37,481 |
| 7 | RAG_Techniques | 29,660 |
| 8 | fastai | 28,210 |
| 9 | handson-ml | 25,604 |
| 10 | fastbook | 25,189 |
| 11 | homemade-machine-learning | 24,807 |
| 12 | GenAI_Agents | 24,441 |
| 13 | pytudes | 24,408 |
| 14 | agents-towards-production | 21,517 |
| 15 | llama-cookbook | 18,559 |
| 16 | awesome-python-applications | 18,077 |
| 17 | mcp-for-beginners | 17,390 |
| 18 | IoT-For-Beginners | 17,110 |
| 19 | vosk-api | 15,159 |
| 20 | Virgilio | 15,000 |
| 21 | python-training | 13,685 |
| 22 | python-machine-learning-book | 12,656 |
| 23 | The-Complete-FAANG-Preparation | 12,277 |
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