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Lucjan Suski, Co-Founder & CEO of Surfer – Interview Series

Unite.AI

When did you initially get interested in search engine optimization? SEO has always fascinated me from the perspective of a product person. Most of the tools that were built in this space had inferior UX compared to what I was used to working as a Product Engineer for several product startups across different fields.

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How to Build an Experiment Tracking Tool [Learnings From Engineers Behind Neptune]

The MLOps Blog

As an MLOps engineer on your team, you are often tasked with improving the workflow of your data scientists by adding capabilities to your ML platform or by building standalone tools for them to use. The focus of this guide is to give you the necessary building blocks to build a tool that works for your team.

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Learnings From Building the ML Platform at Mailchimp

The MLOps Blog

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. Nice to have you here, Miki.

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MLOps Is an Extension of DevOps. Not a Fork — My Thoughts on THE MLOPS Paper as an MLOps Startup CEO

The MLOps Blog

They tackle the ugly problem in the canonical MLOps movement: How do all those MLOps stack components actually relate to each other and work together? In this article, I share how our reality as the MLOps tooling company and my personal views on MLOps agree (and disagree) with it. Came to ML from software. Not a fork.

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Best Machine Learning Datasets

Flipboard

In this post, we’ll show you the datasets you can use to build your machine learning projects. Brief Background of Machine Learning Did you know that machine learning is a part of artificial intelligence that enables computers to learn from data without explicit programming using statistical techniques? Many call this software 2.0.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

How to evaluate MLOps tools and platforms Like every software solution, evaluating MLOps (Machine Learning Operations) tools and platforms can be a complex task as it requires consideration of varying factors. Below, you will find some key factors to consider when assessing MLOps tools and platforms, depending on your needs and preferences.

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Object Detection in 2024: The Definitive Guide

Viso.ai

Get the whitepaper and a demo for your company. The goal of object detection is to develop computational models that provide the most fundamental information needed by computer vision applications : “ What objects are where ?” Most modern person detector techniques are trained on frontal and asymmetric views.