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Top 23 Jupyter Notebook Machine Learning Projects
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Project mention: Ask HN: People who switched from GPT to their own models. How was it? | news.ycombinator.com | 2024-02-26
This is a very nice resource: https://github.com/mlabonne/llm-course
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CodeRabbit
CodeRabbit: AI Code Reviews for Developers. Revolutionize your code reviews with AI. CodeRabbit offers PR summaries, code walkthroughs, 1-click suggestions, and AST-based analysis. Boost productivity and code quality across all major languages with each PR.
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Tensorflow examples
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Project mention: The Top 9️⃣ Repositories to learn Python programming + Resources (Extra) 🤯 | dev.to | 2024-11-06
⭐️ AI For Beginners on GitHub.
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I tested Phi-4 with a Japanese functional test suite and it scored much better than prior Phis (and comparable to much larger models, basically in the top tier atm). [1]
The one red-flag w/ Phi-4 is that it's IFEval score is relatively low. IFEval has specific types of constraints (forbidden words, capitalization, etc) it tests for [2] but its one area especially worth keeping an eye out for those testing Phi-4 for themselves...
[1] https://docs.google.com/spreadsheets/u/3/d/18n--cIaVt49kOh-G...
[2] https://github.com/google-research/google-research/blob/mast...
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CLIP
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
Project mention: We used GPT-4o for image detection with 350 similar illustrations | news.ycombinator.com | 2025-01-14Yes, you could implement image similarity search using embeddings: Create embeddings for the entire image set, save the embeddings in a database, and add embeddings incrementally as new images come in. To search for a similar image, create the embedding for the image that you are looking for and compute the cosine similarity between that embedding and the embeddings in your database. The closer the cosine similarity is to 1.0 the more similar the images.
For choosing a model, the article mentions the AWS Titan multimodal model, but you’d have to pay for API access to create the embeddings. Alternatively, self-hosting the CLIP model [0] to create embeddings would avoid API costs.
Follow-up question: Would the embeddings from the llama3.2-vision models be of higher quality (contain more information) than the original CLIP model?
The llama vision models use CLIP under the hood, but they add a projection head to align with the text model and the CLIP weights are mutated during alignment training, so I assume the llama vision embeddings would be of higher quality, but I don’t know for sure. Does anybody know?
(I would love to test this quality myself but Ollama does not yet support creating image embeddings from the llama vision models - a feature request with several upvotes has been opened [1].)
[0] https://github.com/openai/CLIP
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Project mention: Integrate Hugging Face Spaces & Gradio with a React application | dev.to | 2024-10-12
We are going to use fast.ai to create a simple classification which predicts whether a given image is a cat or not.
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SaaSHub
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Project mention: IA Explicable: Algoritmos y Métodos para Interpretar Modelos de Caja Negra | dev.to | 2024-06-19
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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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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
🌐 Composed Image Retrieval 📎 Intro to Multimodal LLama 3.2 🛠️ Multi Agent Concierge 💻 RAG with Langchain Granite, Milvus 🫶 Download content ✅ Transformer Replacement? 🤖 vLLM for runing models 🌐 Amphion 📝 Autogluon 🚙 Notebook LLama like Google's Notebook LLM 🫶 Monocle2ai for tracing GenAI app code LFA&D Project 🤖 Bee Agent Framework ✅ LLama RFP Response ▶️ GenAI Script 👽 Simular AI Agent S 🦾 DrawDB with AI ✨ Ollama with LLama 3.2 Vision!!!! Preview 🚕 Powerful RAG Checker 📊 SQL Generator 💻 Role of LLMs 🐍 Document Extraction 🕶️ Open Source Vector DB Reddit 🍔 The Practical Guide to Self Hosting LLM 🦾 Stagehand Controller 🕶️ Understanding HNSWLIB 🐍 Best practices in RAG 💻 Enigma Agent 📝 Langchain, Ollama, Phi3 for Function Calling 🔋 Compass Judger 📝 Princeton NLP SimPO 🍔 Princeton NLP ProLong 🔋 Princeton NLP HELMET 🧐 Ollama Cheatsheet 🚕 Princeton NLP CopyCat 📊 Princeton NLP Shp 🕶️ Can LLM Solve Hard Github Issues 📝 Enabling Large Language Models to Generate Text with Citations 🔋 Princeton NLP CharXiv 📊 Awesome AI Agents List 🦾 Nomic’s Matryoshka text embedding model
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FinGPT
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
Project mention: About FinGPT: Open-Source Financial Large Language Models | news.ycombinator.com | 2024-08-28 -
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llm-app
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
Project mention: Show HN: Private RAG with Mistral, Ollama and Pathway | news.ycombinator.com | 2024-07-17We’re excited to share our fully local RAG setup, which has received great feedback from the community.
Full app: https://github.com/pathwaycom/llm-app/tree/main/examples/pip...
We also feature tools and parsers for various RAG use cases, including document parsing with local vision LMs and some other cool stuff.
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python-machine-learning-book
The "Python Machine Learning (1st edition)" book code repository and info resource
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However, let's focus on how to get the assignment done with.
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Project mention: Ask HN: Resources for General Purpose GPU development on Apple's M* chips? | news.ycombinator.com | 2024-12-25
If you're looking for a high level introduction to GPU development on Apple silicon I would recommend learning Metal. It's Apple's GPU acceleration language similar to CUDA for Nvidia hardware. I ported a set of puzzles for CUDA called GPU-Puzzles (a collection of exercises designed to teach GPU programming fundamentals)[1] to Metal [2]. I think it's a very accessible introduction to Metal and writing GPU kernels.
[1] https://github.com/srush/GPU-Puzzles
[2] https://github.com/abeleinin/Metal-Puzzles
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numerical-linear-algebra
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
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amazon-sagemaker-examples
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
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Jupyter Notebook Machine Learning discussion
Jupyter Notebook Machine Learning related posts
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Generative Search for Everyone
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Citations on the Anthropic API
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We used GPT-4o for image detection with 350 similar illustrations
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VerifAI – Generative Search easy to deploy
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Evidently: Open-source ML observability platform
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Boletín OpenSource, November Edition
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What Are Embeddings?
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A note from our sponsor - SaaSHub
www.saashub.com | 8 Feb 2025
Index
What are some of the best open-source Machine Learning projects in Jupyter Notebook? This list will help you:
# | Project | Stars |
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1 | llm-course | 45,659 |
2 | TensorFlow-Examples | 43,493 |
3 | Made-With-ML | 38,126 |
4 | AI-For-Beginners | 35,908 |
5 | google-research | 34,822 |
6 | CLIP | 27,248 |
7 | fastai | 26,584 |
8 | handson-ml | 25,236 |
9 | shap | 23,347 |
10 | homemade-machine-learning | 23,285 |
11 | fastbook | 22,464 |
12 | learnopencv | 21,555 |
13 | llama-cookbook | 16,099 |
14 | FinGPT | 14,797 |
15 | machine-learning-for-trading | 14,032 |
16 | llm-app | 12,628 |
17 | python-machine-learning-book | 12,336 |
18 | mlops-zoomcamp | 11,437 |
19 | ML-Papers-of-the-Week | 10,768 |
20 | GPU-Puzzles | 10,449 |
21 | numerical-linear-algebra | 10,347 |
22 | amazon-sagemaker-examples | 10,272 |
23 | TensorFlow-Tutorials | 9,279 |