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Based on our record, NumPy should be more popular than marimo. It has been mentiond 122 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Pluto is great. I use it all the time. If you like the reactivity/reproducibility but are wedded to Python, you might want to check out Marimo, which is also great. [https://marimo.io/] It too puts the output of a cell above the code so if you're unable to adapt to things that are different it's also probably not for you. FWIW, Observable's Notebooks (Javascript) work the same way: output above the code... - Source: Hacker News / 2 months ago
Marimo notebooks give you the best of both worlds (https://marimo.io). - Source: Hacker News / 4 months ago
Agree with the author, will add: duckdb is an extremely compelling choice if youโre a developer and want to embed analytics in your app (which can also run in a web browser with wasm!) Think this opens up a lot of interesting possibilities like more powerful analytics notebooks like marimo (https://marimo.io/) โฆ and thatโs just one example of many. - Source: Hacker News / 7 months ago
The training pipeline uses Marimo notebooks (think Jupyter, but reactive). Models are quantized to uint8 and served via CDN. Total bundle for a predictor: up-to 2MB. - Source: dev.to / 8 months ago
Marimo is a Jupyter notebook with each cell being somewhat logically connected to each other. That's way if you update the value of a variable in a cell and re-run it, related values in other cells will be auto-updated and auto-run. This is called reactive execution. Thus the notebook can act as a single python script or app and has an extension of .py instead of .ipynb. - Source: dev.to / 9 months ago
Unmatched integration with ML/AI ecosystems through NumPy, TensorFlow, and PyTorch. - Source: dev.to / 10 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 11 months ago
AI starts with math and coding. You donโt need a PhDโjust high school math like algebra and some geometry. Linear algebra (think matrices) and calculus (like slopes) help understand how AI models work. Python is the main language for AI, thanks to tools like TensorFlow and NumPy. If you know JavaScript from Vue.js, Pythonโs syntax is straightforward. - Source: dev.to / about 1 year ago
The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / over 1 year ago
This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / almost 2 years ago
Observable - Interactive code examples/posts
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Hyperquery - Data notebook built for speed, visibility, and collaboration
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Zerve AI - What if Jupyter + Figma + VSCode had a baby?
OpenCV - OpenCV is the world's biggest computer vision library
