The MLOps Blog

JUNE 27, 2023

Data storage and versioning You need data storage and versioning tools to maintain data integrity, enable collaboration, facilitate the reproducibility of experiments and analyses, and ensure accurate ML model development and deployment. Easy collaboration, annotator management, and QA workflows.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

MAY 8, 2024

Before joining AWS India, Vel worked as a Senior DevOps Architect with AWS ProServe North America, supporting major Fortune 500 corporations in the United States. This strategic use of AWS services delivers efficiency and scalability of their operations, as well as the implementation of advanced AI/ML applications.

ML 111

ML Categorization AI AI 111

ODSC - Open Data Science

FEBRUARY 21, 2024

Up-to-dateness In connection with the principle of data consistency (single source of truth), the use of a remote state ensures that configuration changes are based on the latest state. This is critical especially when multiple DevOps team members are working on the configuration.

DevOps 52

DevOps Data Science Metadata Machine Learning 52

Marktechpost

JULY 17, 2023

It can also eliminate data silos by providing a single location for structured, semi-structured, and unstructured data. DataRobot All users, including data science and analytics professionals, IT and DevOps teams, executives, and information workers, can collaborate using DataRobot’s AI Cloud Platform.

Machine Learning 98

Machine Learning Data Mining Data Scientist Data Science 98

Bugra Akyildiz

NOVEMBER 20, 2022

AI for DevOps to infuse AI/ML into the entire software development lifecycle to achieve high productivity. SystemDS is an open source ML system for the end-to-end data science lifecycle from data integration, cleaning, and feature engineering, over efficient, local and distributed ML model training, to deployment and serving.

ML 52

ML Data Science ETL DevOps 52

Heartbeat

MARCH 19, 2024

It involves establishing a standard workflow for training LLMs, fine-tuning (hyper) parameters, deploying them, and collecting and analyzing data (aka response monitoring). Several factors to consider include model output quality, response speed, level of data integrity, and resource and cost constraints.

Large Language Models 52

Large Language Models Prompt Engineering Prompt Engineer Natural Language Processing 52

Marktechpost

JULY 17, 2023

The advantages of using synthetic data include easing restrictions when using private or controlled data, adjusting the data requirements to specific circumstances that cannot be met with accurate data, and producing datasets for DevOps teams to use for software testing and quality assurance.

Machine Learning 52

Machine Learning Data Scientist Computer Vision Deep Learning 52

Viso.ai

MARCH 1, 2023

With low-code, robust security measures, data integration, and cross-platform support are already built-in and can be easily customized. Popular tools, AI models, or frameworks are already integrated and offered to the users without dealing with infrastructure, security, scaling, or DevOps tasks. Low-risk/high ROI.

Computer Vision 52

Computer Vision Software Development AI AI 52

The MLOps Blog

OCTOBER 3, 2023

I switched from analytics to data science, then to machine learning, then to data engineering, then to MLOps. For me, it was a little bit of a longer journey because I kind of had data engineering and cloud engineering and DevOps engineering in between. You shifted straight from data science, if I understand correctly.

ML 52

ML Data Scientist Machine Learning Data Science 52

Unite.AI

NOVEMBER 21, 2024

Archana Joshi brings over 24 years of experience in the IT services industry, with expertise in AI (including generative AI), Agile and DevOps methodologies, and green software initiatives. They rely on pre-existing data rather than providing real-time insights, so it is essential to validate and refine their outputs.

DevOps 144

DevOps Automation Responsible AI Software Development 144

AWS Machine Learning Blog

NOVEMBER 27, 2024

With the Amazon Bedrock serverless experience, you can get started quickly, privately customize FMs with your own data, integrate and deploy them into your application using Amazon Web Services (AWS) tools without having to manage any infrastructure.

Generative AI 96

Generative AI Automation DevOps Prompt Engineer 96