This blog was written in partnership with Run:ai. MLOps – a term that only started to gain steam in 2019 – is big, and only getting bigger. MLOps searches, source: Google Trends. It feels like a new AI / ML... View article
Author: Arseny Kravchenko At Ntropy, machine learning models are the core of our tech and product, and we spend a significant share of our engineering efforts improving them. Aiming for quicker iterations, we are constantly looking for ways to improve the... View article
Run:ai’s 2021 State of AI Infrastructure Survey revealed that 38% of respondents are spending over $1M a year on AI infrastructure (hardware, software, and cloud fees), with 74% of respondents saying that they will increase that spending next year.... View article
This is a project for the MLOps Community to fully understand what Machine Learning Engineers do at their jobs. We want to find out what your day-to-day looks like from the most granular to the most mundane, please tell us... View article
A project for the MLOps Community to fully understand what different people do at their jobs. We want to find out what their day-to-day looks like. Today we shine the spotlight on Mr. James Lamb Machine Learning Extrodinar and LightGBM maintainer... View article
Learning about production ML systems is hard, and getting hands-on experience with them can be even harder. In this post Kyle Gallatin blog breaks down some common components of production ML systems and demonstrates how you can implement simplified versions of them using just Python code.... View article
This blog is written by Vishnu Rachakonda, a Data Scientist at FirstHand. Why I’m writing this Inspired by Ben Kuhn’s Essays on programming I think about a lot, I put together a list of the most influential reads on my... View article
This article is written by Hristo Krastev ( The original post can be found here ). Clearly, no mastermind holds the key. A better place to search might be in the sleepless nights and the overtime hours spent on operationalizing... View article