
Magniv
One line data science infra, Open-Source Python library
Magniv launched on June 1, 2022 with 100 votes, #329 of 3,005 launches that month and more than 75% of that year's launches.
What it does
Today’s data stack was built for yesterday’s software engineers. Data scientists deserve their own tools. Magniv is an open-source Python library that lets data scientists deploy apps independently, without relying on support from software engineers.
Does a similar job
all alternatives →- MOMagniv, One line data science infra2022 · magniv.app · ▲40
Hey HN! We are https://www.magniv.app/ - Magniv is a platform to enable data scientists to autonomously create, deploy, and maintain data applications within existing infra pipelines. That is, reduce data science reliance on data engineers in mature data organizations. While living between both worlds of software engineering and data science, we have seen a lack of mature organizational tooling for data scientists. Data teams either require embedded data engineers or companies are forced to find a unicorn full-stack data software engineer to hire. On top of that, the tooling…

- DAdstack – an open-source tool to build data applications easily2020 · ▲134
Dear HN, I am Riwaj, the cofounder of dstack.ai (https://github.com/dstackai). A few months ago, we built an online service that allows users to publish data visualizations from Python or R. The idea was to build a tool that did not require additional programming or front-end development for publishing data visualizations. Such a code can be invoked from either Jupyter notebook, RMarkdown, Python, or R scripts. Once the data is pushed, it can be accessed via a browser. Open-sourcing dstack: During our customer discovery phase, we realized that dstack.ai should integrate a lot…
- MAMeTA: A Modern C++ Data Sciences Toolkit2014 · meta-toolkit.github.io · ▲39
A Modern C++ Data Sciences Toolkit
An Open-Source Data Science Curriculum2014 · github.com · ▲135The Open Source Data Science Masters. Contribute to datasciencemasters/go development by creating an account on GitHub.
- SPSelf-Published Book – “Data Science in Production”2020 · ▲172
Hi HN, Over the past 6 months I've been working on a technical book focused on helping aspiring data scientists to get hands-on experience with cloud computing environments using the Python ecosystem. The book is targeted at readers already familiar with libraries such as Pandas and scikit-learn that are looking to build out a portfolio of applied projects. To author the book, I used the Leanpub platform to provide drafts of the text as I completed each chapter. To typeset the book, I used the R bookdown package by Yihui Xie to translate my markdown into a PDF format. I also used Google docs…
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