AWS Machine Learning Blog

MAY 9, 2024

The rapid advancements in artificial intelligence and machine learning (AI/ML) have made these technologies a transformative force across industries. An effective approach that addresses a wide range of observed issues is the establishment of an AI/ML center of excellence (CoE). What is an AI/ML CoE?

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AWS Machine Learning Blog

MAY 16, 2024

LotteON aims to be a platform that not only sells products, but also provides a personalized recommendation experience tailored to your preferred lifestyle. LotteON operates various specialty stores, including fashion, beauty, luxury, and kids, and strives to provide a personalized shopping experience across all aspects of customers’ lifestyles.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

To build an enterprise solution, developer resources, cost, time and user-experience have to be balanced to achieve the desired business outcome. Consider revisiting the logging design of the telemetry data and adding infrastructure as code (IaC), such as document processing pipelines, to the solution.

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IBM Journey to AI blog

FEBRUARY 14, 2024

Using machine learning (ML), AI can understand what customers are saying as well as their tone—and can direct them to customer service agents when needed. McDonald’s is building AI solutions for customer care with IBM Watson AI technology and NLP to accelerate the development of its automated order taking (AOT) technology.

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AWS Machine Learning Blog

FEBRUARY 13, 2024

The BigBasket team was running open source, in-house ML algorithms for computer vision object recognition to power AI-enabled checkout at their Fresho (physical) stores. Data augmentation for model training and manually managing the complete end-to-end training cycle was adding significant overhead.

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AWS Machine Learning Blog

NOVEMBER 16, 2023

This is a joint blog with AWS and Philips. Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle. In this post, we describe how Philips partnered with AWS to develop AI ToolSuite—a scalable, secure, and compliant ML platform on SageMaker.

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AWS Machine Learning Blog

OCTOBER 2, 2023

In Part 1 of this series, we drafted an architecture for an end-to-end MLOps pipeline for a visual quality inspection use case at the edge. It is architected to automate the entire machine learning (ML) process, from data labeling to model training and deployment at the edge.

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AWS Machine Learning Blog

SEPTEMBER 1, 2023

ML operationalization summary As defined in the post MLOps foundation roadmap for enterprises with Amazon SageMaker , ML and operations (MLOps) is the combination of people, processes, and technology to productionize machine learning (ML) solutions efficiently.

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AWS Machine Learning Blog

FEBRUARY 1, 2024

In this post, we describe how use generative AI to update and scale your data pipeline using Amazon SageMaker Canvas for data prep. In this post, we describe how use generative AI to update and scale your data pipeline using Amazon SageMaker Canvas for data prep. Prerequisites Before starting, you need an AWS account.

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DataRobot Blog

MARCH 8, 2023

Leveraging DataRobot’s JDBC connectors, enterprise teams can work together to train ML models on their data residing in SAP HANA Cloud and SAP Data Warehouse Cloud, as well as have an option to enrich it with data from external data sources. Tune in to learn more. Registration is free for both events.

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AWS Machine Learning Blog

FEBRUARY 23, 2023

This post covers build approaches, different functional units of ADAS, design approaches to building a modular pipeline, and the challenges of building an ADAS system. End-to-end training – This approach involves training a DNN model that takes raw sensor data as input and outputs the driving command.

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AWS Machine Learning Blog

DECEMBER 13, 2023

Machine learning (ML) models do not operate in isolation. To deliver value, they must integrate into existing production systems and infrastructure, which necessitates considering the entire ML lifecycle during design and development. Building a robust MLOps pipeline demands cross-functional collaboration.

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AWS Machine Learning Blog

DECEMBER 1, 2023

Launched in 2019, Amazon SageMaker Studio provides one place for all end-to-end machine learning (ML) workflows, from data preparation, building and experimentation, training, hosting, and monitoring. SageMaker Studio contains a default private space that only you can access and run in JupyterLab or Code Editor.

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Towards AI

MARCH 28, 2024

This week, I’m super excited to announce that we are finally releasing our book, ‘Building AI for Production; Enhancing LLM Abilities and Reliability with Fine-Tuning and RAG,’ where we gathered all our learnings. Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! AI poll of the week!

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AWS Machine Learning Blog

JUNE 16, 2023

In this post, we discuss how SambaSafety used AWS machine learning (ML) and continuous integration and continuous delivery (CI/CD) tools to deploy their existing data science application for batch inference. At SambaSafety , their mission is to promote safer communities by reducing risk through data insights.

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AWS Machine Learning Blog

MAY 23, 2023

This is a guest blog post co-written with Vik Pant and Kyle Bassett from PwC. With organizations increasingly investing in machine learning (ML), ML adoption has become an integral part of business transformation strategies. Many organizations start their journey into the world of ML with a model-centric viewpoint.

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Towards AI

SEPTEMBER 2, 2023

In this blog, I’ll introduce you to these essential decorators with practical code examples, making your journey into the world of machine learning a little more exciting. This can drastically improve the efficiency of your ML pipelines. __name__} took {end - start} seconds to run.")

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AWS Machine Learning Blog

DECEMBER 7, 2023

In this post, we describe the end-to-end workforce management system that begins with location-specific demand forecast, followed by courier workforce planning and shift assignment using Amazon Forecast and AWS Step Functions. Getir was founded in 2015 and operates in Turkey, the UK, the Netherlands, Germany, and the United States.

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AWS Machine Learning Blog

FEBRUARY 29, 2024

Knowledge Bases for Amazon Bedrock allows you to build performant and customized Retrieval Augmented Generation (RAG) applications on top of AWS and third-party vector stores using both AWS and third-party models. In this post, we demonstrate how to build a RAG workflow using Knowledge Bases for Amazon Bedrock for a drug discovery use case.

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AWS Machine Learning Blog

JULY 6, 2023

Many organizations choose SageMaker as their ML platform because it provides a common set of tools for developers and data scientists. In this post, we cover the benefits for SaaS platforms to integrate with SageMaker, the range of possible integrations, and the process for developing these integrations.

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AWS Machine Learning Blog

AUGUST 14, 2023

This blog post is co-written with Tuana Çelik from deepset. In this post, we showcase how to build an end-to-end generative AI application for enterprise search with Retrieval Augmented Generation (RAG) by using Haystack pipelines and the Falcon-40b-instruct model from Amazon SageMaker JumpStart and Amazon OpenSearch Service.

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Mlearning.ai

APRIL 6, 2023

Automate and streamline our ML inference pipeline with SageMaker and Airflow Building an inference data pipeline on large datasets is a challenge many companies face. The Batch job automatically launches an ML compute instance, deploys the model, and processes the input data in batches, producing the output predictions.

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Towards AI

JULY 21, 2023

Meanwhile back at the ranch… I luckily found my way in creating a training script for adapters (the modular add-ons discussed in last week’s blog). However, Salesforce Research has recently released a unidirectional language model called SimpleTOD, that attempts to solve all the sub-tasks in an end-to-end manner.

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AWS Machine Learning Blog

FEBRUARY 22, 2023

In this post, we discuss how Boomi used the bring-your-own-container (BYOC) approach to develop a new AI/ML enabled solution for their customers to tackle the “blank canvas” problem. Boomi’s ML and data engineering teams needed the solution to be deployed quickly, in a repeatable and consistent way, at scale.

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AWS Machine Learning Blog

JUNE 8, 2023

Data scientists need a consistent and reproducible environment for machine learning (ML) and data science workloads that enables managing dependencies and is secure. This provides a unified end-to-end ML experience across ML developers of varying levels of expertise. An existing SageMaker domain.

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AWS Machine Learning Blog

APRIL 11, 2023

Developing web interfaces to interact with a machine learning (ML) model is a tedious task. With Streamlit , developing demo applications for your ML solution is easy. Streamlit is an open-source Python library that makes it easy to create and share web apps for ML and data science. Create Studio using JupyterLab 3.0

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AWS Machine Learning Blog

NOVEMBER 21, 2023

Amazon SageMaker provides an end-to-end set of services that allow Amazon Music to build, train, and deploy on the AWS Cloud with minimal effort. By taking care of the undifferentiated heavy lifting, SageMaker allows you to focus on working on your machine learning (ML) models, and not worry about things such as infrastructure.

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Bugra Akyildiz

MAY 12, 2024

Articles Apple wrote a blog post that presents a hybrid machine learning approach for personalizing heart rate prediction during exercise by combining a physiological model based on ordinary differential equations (ODEs) with neural networks and representation learning. on heart rate dynamics.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

For decades, Amazon has pioneered and innovated machine learning (ML), bringing delightful experiences to its customers. From the earliest days, Amazon has used ML for various use cases such as book recommendations, search, and fraud detection. In order to achieve this, the M5 team regularly evaluates new techniques to reduce cost.

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AWS Machine Learning Blog

SEPTEMBER 19, 2023

Quantitative modeling and forecasting – Generative models can synthesize large volumes of financial data to train machine learning (ML) models for applications like stock price forecasting, portfolio optimization, risk modeling, and more. One of the ways to handle multi-modal data that is gaining popularity is the use of multi-modal agents.

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Towards AI

JUNE 5, 2023

There are hundreds of blogs written on the same topic. As such, my intention with this blog is not to duplicate those definitions but rather to encourage you to question and evaluate your current ML strategy. While ML algorithms & code play a crucial role in success, it’s just a small piece of the large puzzle.

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AWS Machine Learning Blog

AUGUST 1, 2023

In this post, we demonstrate how you can generate new images from existing base images using Amazon SageMaker , a fully managed service to build, train, and deploy ML models for at scale. Advertising agencies can use generative AI and text-to-image foundation models to create innovative ad creatives and content.

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AWS Machine Learning Blog

NOVEMBER 26, 2023

Whether you’re looking for a managed solution or build your own, you can use these new capabilities to power your journey. Amazon Personalize is a fully managed machine learning (ML) service that makes it easy for developers to deliver personalized experiences to their users.

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AWS Machine Learning Blog

FEBRUARY 7, 2024

In the first post of this three-part series, we presented a solution that demonstrates how you can automate detecting document tampering and fraud at scale using AWS AI and machine learning (ML) services for a mortgage underwriting use case. The following diagram represents each stage in a mortgage document fraud detection pipeline.

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AWS Machine Learning Blog

MARCH 23, 2023

Leidos has partnered with AWS to develop an approach to privacy-preserving, confidential machine learning (ML) modeling where you build cloud-enabled, encrypted pipelines. In this post, we show how to activate privacy-preserving ML predictions for the most highly regulated environments.

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AWS Machine Learning Blog

FEBRUARY 20, 2024

ZOO Digital provides end-to-end localization and media services to adapt original TV and movie content to different languages, regions, and cultures. In this post, we discuss deploying scalable machine learning (ML) models for diarizing media content using Amazon SageMaker , with a focus on the WhisperX model.

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AWS Machine Learning Blog

JANUARY 26, 2024

The goal of this post is to empower AI and machine learning (ML) engineers, data scientists, solutions architects, security teams, and other stakeholders to have a common mental model and framework to apply security best practices, allowing AI/ML teams to move fast without trading off security for speed.

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