AWS Machine Learning Blog

APRIL 6, 2023

& AWS Machine Learning Solutions Lab (MLSL) Machine learning (ML) is being used across a wide range of industries to extract actionable insights from data to streamline processes and improve revenue generation. We trained three models using data from 2011–2018 and predicted the sales values until 2021.

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Hacker News

NOVEMBER 15, 2023

The broad potential is why companies including AWS , IBM , Glean , Google, Microsoft, NVIDIA, Oracle and Pinecone are adopting RAG. But the machine learning engines driving them have grown significantly, increasing their usefulness and popularity.

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AWS Machine Learning Blog

MAY 2, 2023

JumpStart is a machine learning (ML) hub that can help you accelerate your ML journey. There are a few limitations of using off-the-shelf pre-trained LLMs: They’re usually trained offline, making the model agnostic to the latest information (for example, a chatbot trained from 2011–2018 has no information about COVID-19).

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AWS Machine Learning Blog

APRIL 19, 2023

Businesses are increasingly using machine learning (ML) to make near-real-time decisions, such as placing an ad, assigning a driver, recommending a product, or even dynamically pricing products and services. Prerequisites We provide an AWS CloudFormation template to create the prerequisite resources for this solution.

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DagsHub

JULY 25, 2024

Source: Author Introduction Deep learning, a branch of machine learning inspired by biological neural networks, has become a key technique in artificial intelligence (AI) applications. Deep learning methods use multi-layer artificial neural networks to extract intricate patterns from large data sets.

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AWS Machine Learning Blog

JULY 20, 2023

As AI has evolved, we have seen different types of machine learning (ML) models emerge. All these solutions include a meta-estimator (for example in an AWS Lambda function) that invokes each model and implements the blending or voting function. References [1] Raj Kumar, P. Arun; Selvakumar, S. Computer Communications.

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AWS Machine Learning Blog

FEBRUARY 19, 2025

AWS FSI customers, including NASDAQ, State Bank of India, and Bridgewater, have used FMs to reimagine their business operations and deliver improved outcomes. The new Automated Reasoning checks safeguard is available today in preview in Amazon Bedrock Guardrails in the US West (Oregon) AWS Region.

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AWS Machine Learning Blog

NOVEMBER 18, 2024

In this post, we show you how DXC and AWS collaborated to build an AI assistant using large language models (LLMs), enabling users to access and analyze different data types from a variety of data sources. She holds a PhD in theoretical machine learning and enjoys turning cutting-edge research into real-world solutions.

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AWS Machine Learning Blog

NOVEMBER 11, 2024

Solution overview SageMaker JumpStart is a robust feature within the SageMaker machine learning (ML) environment, offering practitioners a comprehensive hub of publicly available and proprietary foundation models (FMs). An AWS Identity and Access Management (IAM) role to access SageMaker.

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