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AWS Machine Learning Blog
FEBRUARY 27, 2024
In this post, we share how Axfood, a large Swedish food retailer, improved operations and scalability of their existing artificial intelligence (AI) and machine learning (ML) operations by prototyping in close collaboration with AWS experts and using Amazon SageMaker. This is a guest post written by Axfood AB.
AWS Machine Learning Blog
APRIL 26, 2023
Do you need help to move your organization’s Machine Learning (ML) journey from pilot to production? Most executives think ML can apply to any business decision, but on average only half of the ML projects make it to production. Challenges Customers may face several challenges when implementing machine learning (ML) solutions.
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AWS Machine Learning Blog
MAY 7, 2024
The service allows for simple audio data ingestion, easy-to-read transcript creation, and accuracy improvement through custom vocabularies. Hugging Face is an open-source machine learning (ML) platform that provides tools and resources for the development of AI projects.
AWS Machine Learning Blog
JUNE 27, 2023
This blog post is co-written with Marat Adayev and Dmitrii Evstiukhin from Provectus. When machine learning (ML) models are deployed into production and employed to drive business decisions, the challenge often lies in the operation and management of multiple models. The models developed by Earth.com lived across various notebooks.
IBM Journey to AI blog
SEPTEMBER 20, 2023
Foundational models (FMs) are marking the beginning of a new era in machine learning (ML) and artificial intelligence (AI) , which is leading to faster development of AI that can be adapted to a wide range of downstream tasks and fine-tuned for an array of applications. Large language models (LLMs) have taken the field of AI by storm.
AWS Machine Learning Blog
MARCH 1, 2023
This combination of great models and continuous adaptation is what will lead to a successful machine learning (ML) strategy. MLOps focuses on the intersection of data science and data engineering in combination with existing DevOps practices to streamline model delivery across the ML development lifecycle.
TensorFlow
JANUARY 18, 2023
Posted by Chansung Park, Sayak Paul (ML and Cloud GDEs) TensorFlow Extended ( TFX ) is a flexible framework allowing Machine Learning (ML) practitioners to iterate on production-grade ML workflows faster with reliability and resiliency. When it comes to ML projects, these changes usually affect the model and/or data.
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