Building Machine Learning Powered ApplicationsEmmanuel Ameisen
Building Machine Learning Powered Applications
by Emmanuel Ameisen · first published 2020
4mentions
3recommended by
4HN commenters
2020–2021first – last mentioned
75% recommend25% neutral
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…engineering and Python, I recommend A Whirlwind Tour Of Python by Jake VanderPlas, and its companion book Python Data Science Handbook. If you're strong in architecting / product management, I recommend Building Machine Learning Powered Applications by Emmanuel Ameisen since it explains it more from an SDLC perspective, including things like scoping, design, development, testing, general software engineering best practices, collaboration, etc. If…
on “The Hundred-Page Machine Learning Book” ↗The latest thinking around 'data science as a product' seems to take this approach. See Building Machine Learning Powered Applications for one resource https://www.oreilly.com/library/view/building-machine-learni...
on “Tips for Shipping Data Products Fast” ↗Disclaimer: This is a book I wrote. Building Machine Learning Powered Applications walks you through building an ML application end-to-end, from product idea to a (simple) deployed version. The free first chapter is available here https://mlpowered.com/book/ The github is at https://github.com/hundredblocks/ml-powered-applications
on “Ask HN: What are some books where the reader learns by building projects?” ↗…projects, or that integrate the foundations of many disciplines into a single project book. Game Engine Black Book: Wolfenstein 3D http://fabiensanglard.net/gebbwolf3d/ Other examples would be things like building Machine Learning Powered Applications, Modern Full-Stack Development,Black Hat Python etc. This was asked last year, and I came into some very interesting reads. I figured it would be worth asking again!
on “Ask HN: Fun Tech Book Recommendations?” ↗