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 129

Data Science Data Drift DevOps Auto-complete 129

AWS Machine Learning Blog

FEBRUARY 27, 2024

This functionality enables us to build generative AI applications in the future for increased understanding of how the model works. Pavel Maslov is a Senior DevOps and ML engineer in the Analytic Platforms team. Pavel has been one of the key players in building the foundational capability within ML at Axfood.

Machine Learning 131

Machine Learning DevOps Data Scientist Data Quality 131

AWS Machine Learning Blog

JUNE 8, 2023

However, businesses can meet this challenge while providing personalized and efficient customer service with the advancements in generative artificial intelligence (generative AI) powered by large language models (LLMs). Generative AI chatbots have gained notoriety for their ability to imitate human intellect.

Generative AI 84

Generative AI LLM Machine Learning Large Language Models 84

AWS Machine Learning Blog

OCTOBER 20, 2023

Customers of every size and industry are innovating on AWS by infusing machine learning (ML) into their products and services. Recent developments in generative AI models have further sped up the need of ML adoption across industries. The architecture maps the different capabilities of the ML platform to AWS accounts.

ML 122

ML Data Scientist ML Engineer Data Science 122

AWS Machine Learning Blog

OCTOBER 22, 2024

You can now create an end-to-end workflow to train, fine tune, evaluate, register, and deploy generative AI models with the visual designer for Amazon SageMaker Pipelines. About the Authors Lauren Mullennex is a Senior AI/ML Specialist Solutions Architect at AWS. Brock Wade is a Software Engineer for Amazon SageMaker.

Automation 81

Automation LLM DevOps Python 81

AWS Machine Learning Blog

FEBRUARY 29, 2024

The AI platform team’s key objective is to ensure seamless access to Workbench services and SageMaker Studio for all Deutsche Bahn teams and projects, with a primary focus on data scientists and ML engineers. Emmanuel Drosos is a Product Owner for the AI platform at DBSystel, a subsidiary of Deutsche Bahn (DB) Germany.

Data Scientist 119

Data Scientist DevOps AI AI 119

AWS Machine Learning Blog

AUGUST 16, 2023

The introduction of generative AI provides another opportunity for Thomson Reuters to work with customers and once again advance how they do their work, helping professionals draw insights and automate workflows, enabling them to focus their time where it matters most.

Large Language Models 86

Large Language Models Machine Learning Generative AI ML 86

AWS Machine Learning Blog

SEPTEMBER 23, 2024

Fortunately, generative AI-powered developer assistants like Amazon Q Developer have emerged to help data scientists streamline their workflows and fast-track ML projects, allowing them to save time and focus on strategic initiatives and innovation. helping customers design and build AI/ML solutions.

ML 81

ML Computer Vision Data Scientist Machine Learning 81

AWS Machine Learning Blog

FEBRUARY 7, 2025

ML engineers Develop model deployment pipelines and control the model deployment processes. ML engineers create the pipelines in Github repositories, and the platform engineer converts them into two different Service Catalog portfolios: ML Admin Portfolio and SageMaker Project Portfolio.

ML 64

ML Data Scientist ML Engineer Data Science 64

AWS Machine Learning Blog

NOVEMBER 21, 2023

His team of scientists and ML engineers is responsible for providing contextually relevant and personalized search results to Amazon Music customers. Siddharth spent early part of his career working with bay area ad-tech startups. Tarun Sharma is a Software Development Manager leading Amazon Music Search Relevance.

ML 101

ML Deep Learning Machine Learning DevOps 101

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. Aurimas: Was it content generation? It’s two things.

ML 52

ML Data Scientist Machine Learning Data Science 52

AWS Machine Learning Blog

NOVEMBER 29, 2023

An evaluation is a task used to measure the quality and responsibility of output of an LLM or generative AI service. Based on this tenet, we can classify generative AI users who need LLM evaluation capabilities into 3 groups as shown in the following figure: model providers, fine-tuners, and consumers.

LLM 103

LLM Data Scientist Algorithm Generative AI 103

Mlearning.ai

MAY 3, 2023

I have Lead & Managed a team of data analysts, business analysts, data engineers, ML engineers, DevOps engineers, and Data Scientists.

Large Language Models 52

Large Language Models Python Auto-complete Natural Language Processing 52