Altexsoft

JULY 23, 2020

When speaking of machine learning, we typically discuss data preparation or model building. What is worse, up to 75 percent of ML projects never go beyond the experimental phase. As a logical reaction to this problem, a new trend — MLOps — has emerged. This article. This article.

Artificial Inteligence 145

Artificial Inteligence Machine Learning DevOps Tools 145

Altexsoft

JUNE 29, 2021

For example, Netflix takes advantage of ML algorithms to personalize and recommend movies for clients, saving the tech giant billions. Google, in turn, uses the Google Neural Machine Translation (GNMT) system, powered by ML, reducing error rates by up to 60 percent. The focus here is on engineering, not on building ML algorithms.

Artificial Inteligence 105

Artificial Inteligence Machine Learning Engineering Data Engineering 105

Altexsoft

FEBRUARY 10, 2021

Unless you meet it in the article saying that “only 13 percent data science projects make it into production.” Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. DataOps vs DevOps.

Analytics 75

Analytics DevOps Development Software Review 75

Altexsoft

MARCH 30, 2023

In this article, we’ll highlight the reasoning behind this choice and the challenges related to it. To dive deeper into details, read our article Data Lakehouse: Concept, Key Features, and Architecture Layers. The answer is simple: They use the same technology to make the most of data. Let’s see what exactly Databricks has to offer.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64