AWS Machine Learning Blog

JANUARY 5, 2024

This post was written in collaboration with Bhajandeep Singh and Ajay Vishwakarma from Wipro’s AWS AI/ML Practice. Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models.

Data Science 103

Data Science Data Drift DevOps Auto-complete 103

Heartbeat

FEBRUARY 1, 2023

Machine Learning Operations (MLOps) are the aspects of ML that deal with the creation and advancement of these models. In this article, we’ll learn everything there is to know about these operations and how ML engineers go about performing them. What is MLOps? Learn more lessons from the field with Comet experts.

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DevOps Machine Learning Data Scientist Software Engineer 96

AWS Machine Learning Blog

FEBRUARY 27, 2024

Apply the trained model to make predictions of future events. Pavel Maslov is a Senior DevOps and ML engineer in the Analytic Platforms team. Pavel has extensive experience in the development of frameworks, infrastructure, and tools in the domains of DevOps and ML/AI on the AWS platform.

Machine Learning 106

Machine Learning DevOps Data Quality Data Scientist 106

AWS Machine Learning Blog

OCTOBER 20, 2023

The architecture maps the different capabilities of the ML platform to AWS accounts. The functional architecture with different capabilities is implemented using a number of AWS services, including AWS Organizations , SageMaker, AWS DevOps services, and a data lake.

ML 95

ML Data Scientist ML Engineer Data Science 95

Heartbeat

OCTOBER 5, 2023

MLOps, often seen as a subset of DevOps (Development Operations), focuses on streamlining the development and deployment of machine learning models. Where is LLMOps in DevOps and MLOps In MLOps, engineers are dedicated to enhancing the efficiency and impact of ML model deployment.

Large Language Models 52

Large Language Models DevOps Prompt Engineer Prompt Engineering 52

AWS Machine Learning Blog

JUNE 8, 2023

A SageMaker real-time inference endpoint enables fast, scalable deployment of ML models for predicting events. Ryan Gomes is a Data & ML Engineer with the AWS Professional Services Intelligence Practice. Solutions Architect at Amazon Web Services with specialization in DevOps and Observability.

Generative AI 71

Generative AI LLM Large Language Models Machine Learning 71

The MLOps Blog

MARCH 21, 2023

As the number of ML-powered apps and services grows, it gets overwhelming for data scientists and ML engineers to build and deploy models at scale. In this comprehensive guide, we’ll explore everything you need to know about machine learning platforms, including: Components that make up an ML platform.

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Machine Learning Data Scientist ML Metadata 69