ARTICLES
The MLOps Stack
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,...
What is a Feature Store
Data teams are starting to realize that operational machine learning requires solving data problems that extend far beyond the creation of data pipelines. In Tecton’s previous post, Why We Need DevOps for ML Data, we highlighted some of the key data challenges that...
A Comprehensive Overview of Natural Language Processing by the Algorithmia team
Everything you need to know about Natural Language Processing.
12 Steps to Reproducible Machine Learning in Production
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...
Building an AI Red Team – Talk at Red Hat OpenShift Commons
At my keyote for the Red Hat OpenShift Commons AI Conference I talked about building an AI Red Team whose job it is to fix AI when it goes wrong. With algorithms making more and more decisions in our lives, from who gets a job, to who gets hired and fired, and even...
Congratulations to Core Pachyderm Member for Raising 16M with Microsoft Venture Arm M12
The AI Infrastructure Alliance congratulates Pachyderm on their successful series B, which saw them raise 16M, led by Microsoft's venture arm, M12, among others. Excerpt below: *** Today, we’re excited to announce we’ve raised $16 million in Series B financing led by...
Building and End-to-End MLOPs platform with Pachyderm, Determined AI and Seldon.
In this excellent tutorial, we walk through how to build and end to end MLOps platform with Determined, Seldon and Pachyderm.
Open Source Myths and Half-Truths: Part 1
In this article from Seldon evangelist, Ryan Dawson, we get a fantastic history of open source and how it's changed in the years since the early Linux revolution. Over time, we've seen a dramatic prolifertion of the new open source models and licenses. In the early...
Will AutoML Replace Data Scientists?
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...
Top Books to Make Yourself a Deep Learning Hero
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