TechCrunch
APRIL 7, 2021
As a company founded by data scientists, Streamlit may be in a unique position to develop tooling to help companies build machine learning applications. Data scientists can download the open-source project and build a machine learning application, but it requires a certain level of technical aptitude to make all the parts work.
DevOps.com
DECEMBER 19, 2023
Here are six distinct technology trends that are poised to be particularly influential for DevOps and software development in the new year.
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InfoWorld
FEBRUARY 15, 2024
Machine learning (ML) is becoming an increasingly important part of the modern application stack. We can build on some of the MLOps concepts used to manage the underlying models, merging them with familiar devops techniques. That means finding ways to test that code, without pushing it to production servers.
Kovair - DevOps
MAY 6, 2022
Views: 35 When discussing AI in software development, we often talk about machine learning. Can machine learning replace DevOps? But is this the same thing?
Speaker: Eran Kinsbruner, Best-Selling Author, TechBeacon Top 30 Test Automation Leader & the Chief Evangelist and Senior Director at Perforce Software
Though DevOps is a relatively new role, it’s one that allows visibility across the whole operation, making it important to senior tech positions. In this session, Eran Kinsbruner will cover recommended areas where artificial intelligence and machine learning can be leveraged.
Dzone - DevOps
JANUARY 19, 2022
AI/ML and DevOps are hot buzzwords in the tech industry right now. Thus, demand for Artificial intelligence, machine learning, and DevOps is picking up an increased pace every hour. Thus, demand for Artificial intelligence, machine learning, and DevOps is picking up an increased pace every hour.
DevOps.com
MARCH 12, 2024
The integration of AI and ML in testing is a fundamental shift in how we approach software quality and reliability in DevOps environments.
Advertiser: Data Robot
And more is being asked of data scientists as companies look to implement artificial intelligence (AI) and machine learning technologies into key operations. Fostering collaboration between DevOps and machine learning operations (MLOps) teams. Sharing data with trusted partners and suppliers to ensure top value.
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