by Valoh AI | Oct 12, 2020 | Infrastructure, MLOps
What is MLOps (briefly) MLOps is a set of best practices that revolve around making machine learning in production more seamless. The purpose is to bridge the gap between experimentation and production with key principles to make machine learning reproducible,...
by Maiot | Sep 12, 2020 | Infrastructure, MLOps
The last two decades have yielded us some great understandings about Software Development. A big part of that is due to the emergence of DevOps and it’s wide adoption throughout the industry. Leading software companies follow identical patterns: Fast iterations in...
by Determined AI | Aug 16, 2020 | Infrastructure, MLOps
In this excellent tutorial from the Determined AI team, evangelist David Hersey walks through crafting an end to end machine learning pipeline and how to: Create data repositories with Pachyderm, using Pachyderm data pipelines to prepare the data for training Build a...
by Daniel Jeffries | Jul 10, 2020 | AutoML, Infrastructure
In this article, KD Nuggets authors Joseph Chin, Aifaz Gowani, Gabriel James, and Matthew Peng ask if AutoML services from Amazon, Google and Microsoft will replace data scientists in the long run. The data science pipeline is a complicated one with a lot of manual...
by AI Infrastructure Alliance | Mar 7, 2020 | AI Hardware, Infrastructure, MLOps
It’s an amazing time for data scientists everywhere, as the hardware needed to crunch numbers like never before comes online. It wasn’t long ago that there were only a few chip manufacturers in the world, Intel and AMD, working on essentially the same...
by Daniel Jeffries | Sep 30, 2019 | Infrastructure, MLOps, Open Source
There’s an exciting side to AI. Intense, multi-million dollar research over many years that leads to a billion dollar algorithmic breakthrough that keeps self-driving cars from crashing or detects lung cancer better than ever is glamorous part of intelligent...
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