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AI coding just arrived in Jupyter notebooks - and bhupesh ganger (Jupyter co-founder) and I will show you how to use it. Coding by hand is becoming obsolete. The latest Jupyter AI - built by the Jupyter team and showcased at JupyterCon this week - brings AI assistance directly...

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Andrew Ng

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118,362 Aufrufe • vor 9 Monaten •via X (Twitter)

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I'm reiterating - I think a better interface for LLMs on desktop is an interactive notebook, not chat. I'm trying to build a better intuition for PCA and strongly feel an interactive notebook where I'm chatting with LLM + also modifying code/plotting figures is a much better interaction. Bonus points if you make notebook cells branchable (so if you get an error, you can ask LLM to fix it without adding that rotten context to the main branch of learning). Please steal this idea. Make an AI-powered, interactive, branching notebook.
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Paras Chopra

58,232 Aufrufe • vor 11 Monaten

The era of manually analyzing data will come to an end. AI can now do a lot of this automatically. It's a huge time saver. I do data analysis for a living, and I'm a huge fan of writing Jupyter notebooks to do it all, but it's now hard to justify manually writing code that you can generate in a few seconds. I still check everything manually, but breaking down datasets into tables and charts is now 10x easier than it's ever been. Here is a video where I'm using Retool. I load a dataset and generate a few charts as quickly as I can think. The speed at which we can go from one idea to a working solution is astonishing.
4:35

The era of manually analyzing data will come to an end. AI can now do a lot of this automatically. It's a huge time saver. I do data analysis for a living, and I'm a huge fan of writing Jupyter notebooks to do it all, but it's now hard to justify manually writing code that you can generate in a few seconds. I still check everything manually, but breaking down datasets into tables and charts is now 10x easier than it's ever been. Here is a video where I'm using Retool. I load a dataset and generate a few charts as quickly as I can think. The speed at which we can go from one idea to a working solution is astonishing.

Santiago

70,812 Aufrufe • vor 10 Monaten

🎯 AI Agents for Microsoft Planetary Computer: Explore Satellite Data with Zero Code Unlock satellite data without writing a single line of code! 🌍 In this step-by-step tutorial, you’ll discover how to harness the power of AI agents to search, filter, and visualize geospatial datasets from the Microsoft Planetary Computer — all using natural language. Perfect for researchers, developers, and environmental professionals who want fast, intuitive, code-free access to massive Earth observation datasets like Sentinel-2, Landsat, NAIP, and DEM. Learn how to: ✅ Use zero-code AI agents in Jupyter Notebooks ✅ Search satellite imagery by date, location, or cloud cover ✅ Visualize data instantly using Leafmap ✅ Integrate STAC data catalogs into your GeoAI workflow Full video tutorial available on YouTube: #geospatial #GeoAI #opensource #PlanetaryComputer
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🎯 AI Agents for Microsoft Planetary Computer: Explore Satellite Data with Zero Code Unlock satellite data without writing a single line of code! 🌍 In this step-by-step tutorial, you’ll discover how to harness the power of AI agents to search, filter, and visualize geospatial datasets from the Microsoft Planetary Computer — all using natural language. Perfect for researchers, developers, and environmental professionals who want fast, intuitive, code-free access to massive Earth observation datasets like Sentinel-2, Landsat, NAIP, and DEM. Learn how to: ✅ Use zero-code AI agents in Jupyter Notebooks ✅ Search satellite imagery by date, location, or cloud cover ✅ Visualize data instantly using Leafmap ✅ Integrate STAC data catalogs into your GeoAI workflow Full video tutorial available on YouTube: #geospatial #GeoAI #opensource #PlanetaryComputer

Qiusheng Wu

10,346 Aufrufe • vor 10 Monaten