AWS Machine Learning Blog

MAY 31, 2023

Getting AWS Certified can help you propel your career, whether you’re looking to find a new role, showcase your skills to take on a new project, or become your team’s go-to expert. Reading the FAQ page of the AWS services relevant for your certification exam is important in order to acquire a deeper understanding of the service.

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AWS Machine Learning Blog

MARCH 30, 2023

Not only was he widely considered the top-rated goalkeeper in the league during the 2021/22 season, but he also held that title back in 2018/19 when Eintracht Frankfurt reached the Europa League semifinals. The result is a machine learning (ML)-powered insight that allows fans to easily evaluate and compare the goalkeepers’ proficiencies.

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AWS Machine Learning Blog

FEBRUARY 6, 2024

To support overarching pharmacovigilance activities, our pharmaceutical customers want to use the power of machine learning (ML) to automate the adverse event detection from various data sources, such as social media feeds, phone calls, emails, and handwritten notes, and trigger appropriate actions.

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AWS Machine Learning Blog

JUNE 26, 2024

This post is a follow-up to Generative AI and multi-modal agents in AWS: The key to unlocking new value in financial markets. This blog is part of the series, Generative AI and AI/ML in Capital Markets and Financial Services. Delete the S3 buckets created by AWS CloudFormation and then delete the CloudFormation stack.

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AWS Machine Learning Blog

OCTOBER 21, 2024

Amazon Bedrock Agents allows you to write IaC code with AWS CloudFormation , the AWS Cloud Development Kit (AWS CDK), or Terraform. We provide blueprint templates of the most common capabilities of Amazon Bedrock Agents, which can be deployed and updated with a single AWS CDK command.

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AWS Machine Learning Blog

APRIL 19, 2023

Since 2018, our team has been developing a variety of ML models to enable betting products for NFL and NCAA football. These models are then pushed to an Amazon Simple Storage Service (Amazon S3) bucket using DVC, a version control tool for ML models. Business requirements We are the US squad of the Sportradar AI department.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

These activities cover disparate fields such as basic data processing, analytics, and machine learning (ML). ML is often associated with PBAs, so we start this post with an illustrative figure. The ML paradigm is learning followed by inference. The union of advances in hardware and ML has led us to the current day.

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Flipboard

FEBRUARY 2, 2023

With advanced analytics derived from machine learning (ML), the NFL is creating new ways to quantify football, and to provide fans with the tools needed to increase their knowledge of the games within the game of football. We then explain the details of the ML methodology and model training procedures.

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AWS Machine Learning Blog

MARCH 14, 2024

In this post we highlight how the AWS Generative AI Innovation Center collaborated with the AWS Professional Services and PGA TOUR to develop a prototype virtual assistant using Amazon Bedrock that could enable fans to extract information about any event, player, hole or shot level details in a seamless interactive manner.

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AWS Machine Learning Blog

SEPTEMBER 23, 2024

Since its launch in 2018, Just Walk Out technology by Amazon has transformed the shopping experience by allowing customers to enter a store, pick up items, and leave without standing in line to pay. About the Authors Tian Lan is a Principal Scientist at AWS. Chris Broaddus is a Senior Manager at AWS.

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AWS Machine Learning Blog

FEBRUARY 5, 2024

SageMaker geospatial capabilities make it easy for data scientists and machine learning (ML) engineers to build, train, and deploy models using geospatial data. Incorporating ML with geospatial data enhances the capability to detect anomalies and unusual patterns systematically, which is essential for early warning systems.

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AWS Machine Learning Blog

OCTOBER 2, 2024

Additionally, check out the service introduction video from AWS re:Invent 2023. About the Authors Maira Ladeira Tanke is a Senior Generative AI Data Scientist at AWS. Mark Roy is a Principal Machine Learning Architect for AWS, helping customers design and build generative AI solutions.

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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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AWS Machine Learning Blog

AUGUST 16, 2023

Training machine learning (ML) models to interpret this data, however, is bottlenecked by costly and time-consuming human annotation efforts. The images document the land cover, or physical surface features, of ten European countries between June 2017 and May 2018. The following are a few example RGB images and their labels.

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AWS Machine Learning Blog

FEBRUARY 10, 2023

Through a collaboration between the Next Gen Stats team and the Amazon ML Solutions Lab , we have developed the machine learning (ML)-powered stat of coverage classification that accurately identifies the defense coverage scheme based on the player tracking data. In this post, we deep dive into the technical details of this ML model.

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AWS Machine Learning Blog

MARCH 30, 2023

Amazon Personalize is a fully managed machine learning (ML) service that makes it easy for developers to deliver personalized experiences to their users. You can get started without any prior ML experience, using APIs to easily build sophisticated personalization capabilities in a few clicks. Choose the new aws-trending-now recipe.

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AWS Machine Learning Blog

APRIL 3, 2023

Prerequisites You need an AWS account to use this solution. To run this JumpStart 1P Solution and have the infrastructure deployed to your AWS account, you need to create an active Amazon SageMaker Studio instance (refer to Onboard to Amazon SageMaker Domain ). The following figure illustrates these metrics.

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AWS Machine Learning Blog

FEBRUARY 8, 2023

Machine learning (ML) has become ubiquitous. Our customers are employing ML in every aspect of their business, including the products and services they build, and for drawing insights about their customers. To build an ML-based application, you have to first build the ML model that serves your business requirement.

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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

MAY 5, 2023

This is a joint post co-written by AWS and Voxel51. Solution overview Ground Truth is a fully self-served and managed data labeling service that empowers data scientists, machine learning (ML) engineers, and researchers to build high-quality datasets. A retail company is building a mobile app to help customers buy clothes.

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AWS Machine Learning Blog

NOVEMBER 21, 2023

Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from any document or image. Anjan is part of the worldwide AI services specialist team and works with customers to help them understand and develop solutions to business problems with AWS AI Services and generative AI.

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Chatbots Life

MAY 16, 2023

Master of Code Global (MOCG) is a certified partner of Microsoft and AWS and has been recognized by LivePerson, Inc. 10Clouds is a software consultancy, development, ML, and design house based in Warsaw, Poland. 10Clouds provides a wide range of services related to digital product development and design, including blockchain services.

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Mlearning.ai

JANUARY 26, 2023

BUILDING EARTH OBSERVATION DATA CUBES ON AWS. 2018, July). In IGARSS 2018–2018 IEEE International Geoscience and Remote Sensing Symposium (pp. AWS , GCP , Azure , CreoDIAS , for example, are not open-source, nor are they “standard”. Big ones can: AWS is benefiting a lot from these concepts. Data, 4(3), 92.

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AWS Machine Learning Blog

JULY 13, 2023

PMLR, 2018. [2] arXiv preprint arXiv:1810.03264 (2018). [4] About the Author Uri Rosenberg is the AI & ML Specialist Technical Manager for Europe, Middle East, and Africa. Based out of Israel, Uri works to empower enterprise customers to design, build, and operate ML workloads at scale. 3] Dai, Wei, et al.

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Alation

SEPTEMBER 30, 2022

Our ability to leverage ML for each allows us to make operations teams far more efficient. The Forrester Wave: Machine Data Learning Catalogs, Q2 2018. Our comprehensive connectors mean that we can build lineage much more efficiently. We have evolved the product to support more use cases and more user types.

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AWS Machine Learning Blog

MAY 22, 2023

Prerequisites To get started, all you need is an AWS account in which you can use Studio. About the authors Laurent Callot is a Principal Applied Scientist and manager at AWS AI Labs who has worked on a variety of machine learning problems, from foundational models and generative AI to forecasting, anomaly detection, causality, and AI Ops.

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Alation

MARCH 21, 2023

When it embarked on a digital transformation and modernization initiative in 2018, the company migrated all its data to AWS S3 Data Lake and Snowflake Data Cloud to provide accessibility to data to all users. Using Alation, ARC automated the data curation and cataloging process.

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AWS Machine Learning Blog

JULY 9, 2024

of its consolidated revenues during the years ended December 31, 2019, 2018 and 2017, respectively. Currently he helps customers in the financial service and insurance industry build machine learning solutions on AWS. Scott Mullins is Managing Director and General Manger of AWS’ Worldwide Financial Services organization.

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O'Reilly Media

NOVEMBER 28, 2023

How will AI adopters react when the cost of renting infrastructure from AWS, Microsoft, or Google rises? The next most needed skill is operations for AI and ML (54%). We’re glad to see people recognize this; we’ve long thought that operations was the “elephant in the room” for AI and ML. But they may back off on AI development.

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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. You can access the Meta Llama 3.2

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The MLOps Blog

JULY 18, 2023

This article was originally an episode of the MLOps Live , an interactive Q&A session where ML practitioners answer questions from other ML practitioners. Every episode is focused on one specific ML topic, and during this one, we talked to Jason Falks about deploying conversational AI products to production.

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AWS Machine Learning Blog

JANUARY 17, 2024

Today, we’re excited to announce the availability of Llama 2 inference and fine-tuning support on AWS Trainium and AWS Inferentia instances in Amazon SageMaker JumpStart. In this post, we demonstrate how to deploy and fine-tune Llama 2 on Trainium and AWS Inferentia instances in SageMaker JumpStart.

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AWS Machine Learning Blog

AUGUST 7, 2023

In an effort to create and maintain a socially responsible gaming environment, AWS Professional Services was asked to build a mechanism that detects inappropriate language (toxic speech) within online gaming player interactions. Unfortunately, as in the real world, not all players communicate appropriately and respectfully.

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Flipboard

APRIL 13, 2023

The seeds of a machine learning (ML) paradigm shift have existed for decades, but with the ready availability of scalable compute capacity, a massive proliferation of data, and the rapid advancement of ML technologies, customers across industries are transforming their businesses.

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AWS Machine Learning Blog

FEBRUARY 29, 2024

In this post, we investigate of potential for the AWS Graviton3 processor to accelerate neural network training for ThirdAI’s unique CPU-based deep learning engine. As shown in our results, we observed a significant training speedup with AWS Graviton3 over the comparable Intel and NVIDIA instances on several representative modeling workloads.

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Flipboard

NOVEMBER 24, 2023

In this post, we show you how SnapLogic , an AWS customer, used Amazon Bedrock to power their SnapGPT product through automated creation of these complex DSL artifacts from human language. SnapLogic background SnapLogic is an AWS customer on a mission to bring enterprise automation to the world.

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AWS Machine Learning Blog

NOVEMBER 14, 2023

Examples include: Cultivating distrust in the media Undermining the democratic process Spreading false or discredited science (for example, the anti-vax movement) Advances in artificial intelligence (AI) and machine learning (ML) have made developing tools for creating and sharing fake news even easier.

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