AWS Machine Learning Blog

JANUARY 7, 2025

The translation playground could be adapted into a scalable serverless solution as represented by the following diagram using AWS Lambda , Amazon Simple Storage Service (Amazon S3), and Amazon API Gateway. To run the project code, make sure that you have fulfilled the AWS CDK prerequisites for Python.

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AWS Machine Learning Blog

APRIL 3, 2025

At the heart of this transformation is the OMRON Data & Analytics Platform (ODAP), an innovative initiative designed to revolutionize how the company harnesses its data assets. The robust security features provided by Amazon S3, including encryption and durability, were used to provide data protection.

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AWS Machine Learning Blog

OCTOBER 24, 2024

Amazon QuickSight powers data-driven organizations with unified (BI) at hyperscale. With QuickSight, all users can meet varying analytic needs from the same source of truth through modern interactive dashboards, paginated reports, embedded analytics, and natural language queries. Choose Create stack.

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Flipboard

NOVEMBER 7, 2023

“Data is at the center of every application, process, and business decision,” wrote Swami Sivasubramanian, VP of Database, Analytics, and Machine Learning at AWS, and I couldn’t agree more. A common pattern customers use today is to build data pipelines to move data from Amazon Aurora to Amazon Redshift.

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AWS Machine Learning Blog

DECEMBER 4, 2024

SageMaker Unified Studio combines various AWS services, including Amazon Bedrock , Amazon SageMaker , Amazon Redshift , Amazon Glue , Amazon Athena , and Amazon Managed Workflows for Apache Airflow (MWAA) , into a comprehensive data and AI development platform. Navigate to the AWS Secrets Manager console and find the secret -api-keys.

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AWS Machine Learning Blog

FEBRUARY 21, 2025

Lets assume that the question What date will AWS re:invent 2024 occur? The corresponding answer is also input as AWS re:Invent 2024 takes place on December 26, 2024. If the question was Whats the schedule for AWS events in December?, This setup uses the AWS SDK for Python (Boto3) to interact with AWS services.

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Data Science Dojo

JULY 6, 2023

Data engineering tools are software applications or frameworks specifically designed to facilitate the process of managing, processing, and transforming large volumes of data. Amazon Redshift: Amazon Redshift is a cloud-based data warehousing service provided by Amazon Web Services (AWS).

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AWS Machine Learning Blog

OCTOBER 18, 2023

This post details how Purina used Amazon Rekognition Custom Labels , AWS Step Functions , and other AWS Services to create an ML model that detects the pet breed from an uploaded image and then uses the prediction to auto-populate the pet attributes. AWS CodeBuild is a fully managed continuous integration service in the cloud.

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IBM Journey to AI blog

MAY 15, 2024

Data must be combined and harmonized from multiple sources into a unified, coherent format before being used with AI models. Unified, governed data can also be put to use for various analytical, operational and decision-making purposes. This process is known as data integration, one of the key components to a strong data fabric.

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AWS Machine Learning Blog

SEPTEMBER 18, 2024

ZOE is a multi-agent LLM application that integrates with multiple data sources to provide a unified view of the customer, simplify analytics queries, and facilitate marketing campaign creation. Additionally, Feast promotes feature reuse, so the time spent on data preparation is reduced greatly.

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Pickl AI

DECEMBER 26, 2024

Summary: “Data Science in a Cloud World” highlights how cloud computing transforms Data Science by providing scalable, cost-effective solutions for big data, Machine Learning, and real-time analytics. In Data Science in a Cloud World, we explore how cloud computing has revolutionised Data Science.

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AWS Machine Learning Blog

MARCH 1, 2023

This post is co-written with Suhyoung Kim, General Manager at KakaoGames Data Analytics Lab. In this post, we share how Kakao Games and the Amazon Machine Learning Solutions Lab teamed up to build a scalable and reliable LTV prediction solution by using AWS data and ML services such as AWS Glue and Amazon SageMaker.

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Precisely

APRIL 11, 2024

In an era where cloud technology is not just an option but a necessity for competitive business operations, the collaboration between Precisely and Amazon Web Services (AWS) has set a new benchmark for mainframe and IBM i modernization. Solution page Precisely on Amazon Web Services (AWS) Precisely brings data integrity to the AWS cloud.

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Flipboard

NOVEMBER 24, 2023

In this post, we will talk about how BMW Group, in collaboration with AWS Professional Services, built its Jupyter Managed (JuMa) service to address these challenges. For example, teams using these platforms missed an easy migration of their AI/ML prototypes to the industrialization of the solution running on AWS.

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AWS Machine Learning Blog

OCTOBER 23, 2024

SnapLogic uses Amazon Bedrock to build its platform, capitalizing on the proximity to data already stored in Amazon Web Services (AWS). Control plane and data plane implementation SnapLogic’s Agent Creator platform follows a decoupled architecture, separating the control plane and data plane for enhanced security and scalability.

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The MLOps Blog

MAY 17, 2023

We also discuss different types of ETL pipelines for ML use cases and provide real-world examples of their use to help data engineers choose the right one. What is an ETL data pipeline in ML? Xoriant It is common to use ETL data pipeline and data pipeline interchangeably.

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AWS Machine Learning Blog

FEBRUARY 5, 2025

The following diagram illustrates the data pipeline for indexing and query in the foundational search architecture. The listing indexer AWS Lambda function continuously polls the queue and processes incoming listing updates. He has specialization in data strategy, machine learning and Generative AI.

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phData

AUGUST 6, 2024

As today’s world keeps progressing towards data-driven decisions, organizations must have quality data created from efficient and effective data pipelines. For customers in Snowflake, Snowpark is a powerful tool for building these effective and scalable data pipelines.

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Smart Data Collective

SEPTEMBER 8, 2021

The data is initially extracted from a vast array of sources before transforming and converting it to a specific format based on business requirements. ETL is one of the most integral processes required by Business Intelligence and Analytics use cases since it relies on the data stored in Data Warehouses to build reports and visualizations.

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ODSC - Open Data Science

APRIL 23, 2025

Confluent Confluent provides a robust data streaming platform built around Apache Kafka. AI credits from Confluent can be used to implement real-time data pipelines, monitor data flows, and run stream-based ML applications. Explore Real-Time and Streaming Data UseCases Tools like Confluent and Vespa.ai

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AWS Machine Learning Blog

JUNE 18, 2024

On December 6 th -8 th 2023, the non-profit organization, Tech to the Rescue , in collaboration with AWS, organized the world’s largest Air Quality Hackathon – aimed at tackling one of the world’s most pressing health and environmental challenges, air pollution. As always, AWS welcomes your feedback.

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AWS Machine Learning Blog

AUGUST 12, 2024

Furthermore, the democratization of AI and ML through AWS and AWS Partner solutions is accelerating its adoption across all industries. For example, a health-tech company may be looking to improve patient care by predicting the probability that an elderly patient may become hospitalized by analyzing both clinical and non-clinical data.

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AWS Machine Learning Blog

FEBRUARY 13, 2024

SageMaker Feature Store now makes it effortless to share, discover, and access feature groups across AWS accounts. With this launch, account owners can grant access to select feature groups by other accounts using AWS Resource Access Manager (AWS RAM). Their task is to construct and oversee efficient data pipelines.

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AWS Machine Learning Blog

SEPTEMBER 24, 2024

Working with the AWS Generative AI Innovation Center , DoorDash built a solution to provide Dashers with a low-latency self-service voice experience to answer frequently asked questions, reducing the need for live agent assistance, in just 2 months. You can deploy the solution in your own AWS account and try the example solution.

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Flipboard

AUGUST 17, 2023

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. To do this, we provide an AWS CloudFormation template to create a stack that contains the resources.

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AWS Machine Learning Blog

DECEMBER 20, 2023

Whether logs are coming from Amazon Web Services (AWS), other cloud providers, on-premises, or edge devices, customers need to centralize and standardize security data. After the security log data is stored in Amazon Security Lake, the question becomes how to analyze it. Subscribe an AWS Lambda function to the SQS queue.

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AWS Machine Learning Blog

FEBRUARY 24, 2023

AWS recently released Amazon SageMaker geospatial capabilities to provide you with satellite imagery and geospatial state-of-the-art machine learning (ML) models, reducing barriers for these types of use cases. In the following sections, we dive into each pipeline in more detail.

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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

MARCH 8, 2023

In order to train a model using data stored outside of the three supported storage services, the data first needs to be ingested into one of these services (typically Amazon S3). This requires building a data pipeline (using tools such as Amazon SageMaker Data Wrangler ) to move data into Amazon S3.

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AWS Machine Learning Blog

DECEMBER 15, 2023

Amazon SageMaker Canvas is a no-code ML workspace offering ready-to-use models, including foundation models, and the ability to prepare data and build and deploy custom models. In this post, we discuss how to bring data stored in Amazon DocumentDB into SageMaker Canvas and use that data to build ML models for predictive analytics.

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AWS Machine Learning Blog

OCTOBER 7, 2024

By using the natural language processing and generation capabilities of generative AI, the chat assistant can understand user queries, retrieve relevant information from various data sources, and provide tailored, contextual responses. See Data source connectors for a list of supported data source connectors for Amazon Kendra.

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Smart Data Collective

AUGUST 17, 2022

Kafka And ETL Processing: You might be using Apache Kafka for high-performance data pipelines, stream various analytics data, or run company critical assets using Kafka, but did you know that you can also use Kafka clusters to move data between multiple systems. Step 2: Create a Data Catalog table.

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AWS Machine Learning Blog

APRIL 12, 2023

In this post, we describe how AWS Partner Airis Solutions used Amazon Lookout for Equipment , AWS Internet of Things (IoT) services, and CloudRail sensor technologies to provide a state-of-the-art solution to address these challenges. It’s an easy way to run analytics on IoT data to gain accurate insights.

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AWS Machine Learning Blog

DECEMBER 6, 2023

This is especially true for questions that require analytical reasoning across multiple documents. This task involves answering analytical reasoning questions. In this post, we show how to design an intelligent document assistant capable of answering analytical and multi-step reasoning questions in three parts.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

The financial services industry (FSI) is no exception to this, and is a well-established producer and consumer of data and analytics. These activities cover disparate fields such as basic data processing, analytics, and machine learning (ML). Suppliers of data center GPUs include NVIDIA, AMD, Intel, and others.

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AWS Machine Learning Blog

AUGUST 21, 2024

Output collection and analysis – Retrieve processed results and integrate them into existing workflows or analytics systems. By walking through this specific implementation, we aim to showcase how you can adapt batch inference to suit various data processing needs, regardless of the data source or nature.

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AWS Machine Learning Blog

AUGUST 8, 2024

As one of the largest AWS customers, Twilio engages with data, artificial intelligence (AI), and machine learning (ML) services to run their daily workloads. Data is the foundational layer for all generative AI and ML applications. Access to Amazon Bedrock FMs isn’t granted by default.

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