AWS Machine Learning Blog

OCTOBER 6, 2023

One such component is a feature store, a tool that stores, shares, and manages features for machine learning (ML) models. Features are the inputs used during training and inference of ML models. Amazon SageMaker Feature Store is a fully managed repository designed specifically for storing, sharing, and managing ML model features.

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AWS Machine Learning Blog

JUNE 3, 2024

Solution overview SageMaker Canvas brings together a broad set of capabilities to help data professionals prepare, build, train, and deploy ML models without writing any code. based single sign-on (SSO) methods, such as AWS IAM Identity Center. You can also use your organization’s SAML 2.0-based Choose Create.

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AWS Machine Learning Blog

OCTOBER 17, 2023

At Amazon Web Services (AWS) , not only are we passionate about providing customers with a variety of comprehensive technical solutions, but we’re also keen on deeply understanding our customers’ business processes. This method is called working backwards at AWS. Project background Milk is a nutritious beverage.

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IBM Journey to AI blog

NOVEMBER 13, 2023

Developed internally at Google and released to the public in 2014, Kubernetes has enabled organizations to move away from traditional IT infrastructure and toward the automation of operational tasks tied to the deployment, scaling and managing of containerized applications (or microservices ).

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AWS Machine Learning Blog

MAY 7, 2024

Founded in 2014, Veritone empowers people with AI-powered software and solutions for various applications, including media processing, analytics, advertising, and more. The processed videos are sent to AWS services like Amazon Rekognition, Amazon Transcribe, and Amazon Comprehend to generate metadata at shot level and video level.

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AWS Machine Learning Blog

NOVEMBER 15, 2023

Segment Anything Model (SAM) Foundation models are large machine learning (ML) models trained on vast quantity of data and can be prompted or fine-tuned for task-specific use cases. Amazon SageMaker is a fully managed ML platform that enables builders to explore large language and visual models and build generative AI applications.

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AWS Machine Learning Blog

JANUARY 25, 2023

Model explainability refers to the process of relating the prediction of a machine learning (ML) model to the input feature values of an instance in humanly understandable terms. Amazon SageMaker Clarify is a feature of Amazon SageMaker that enables data scientists and ML engineers to explain the predictions of their ML models.

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DagsHub

APRIL 7, 2024

These pipelines cover the entire lifecycle of an ML project, from data ingestion and preprocessing, to model training, evaluation, and deployment. Adopted from [link] In this article, we will first briefly explain what ML workflows and pipelines are. around the world to streamline their data and ML pipelines.

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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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AWS Machine Learning Blog

JULY 13, 2023

Advances in neural information processing systems 27 (2014). 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.

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DagsHub

OCTOBER 23, 2024

Managing unstructured data is essential for the success of machine learning (ML) projects. This article will discuss managing unstructured data for AI and ML projects. You will learn the following: Why unstructured data management is necessary for AI and ML projects. How to properly manage unstructured data.

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Heartbeat

FEBRUARY 27, 2023

AWS, Google Cloud, and Azure are a few well-known cloud service providers that provide pre-built GANs and DRL frameworks for creating and deploying models on their cloud platforms. When choosing a framework, it is critical to consider both the users’ level of experience and the specific requirements of the task at hand.

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The MLOps Blog

OCTOBER 20, 2023

And that’s what we’re going to focus on in this article, which is the second in my series on Software Patterns for Data Science & ML Engineering. In 2014, Project Jupyter evolved from IPython. interactive dashboards help ML teams to collaborate and share experiment results with stakeholders across the company. Aside neptune.ai

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ODSC - Open Data Science

JANUARY 29, 2024

GANs, introduced in 2014 paved the way for GenAI with models like Pix2pix and DiscoGAN. Open Source ML/DL Platforms: Pytorch, Tensorflow, and scikit-learn Hiring managers continue to favor the most popular open-source machine/deep learning platforms including Pytorch, Tensorflow, and scikit-learn.

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AWS Machine Learning Blog

APRIL 5, 2024

SageMaker geospatial capabilities make it straightforward for data scientists and machine learning (ML) engineers to build, train, and deploy models using geospatial data. Among these models, the spatial fixed effect model yielded the highest mean R-squared value, particularly for the timeframe spanning 2014 to 2020.

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AWS Machine Learning Blog

JULY 9, 2024

Currently he helps customers in the financial service and insurance industry build machine learning solutions on AWS. Joe Dunn is an AWS Principal Solutions Architect in Financial Services with over 20 years of experience in infrastructure architecture and migration of business-critical loads to AWS.

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AWS Machine Learning Blog

DECEMBER 4, 2024

Building generative AI applications presents significant challenges for organizations: they require specialized ML expertise, complex infrastructure management, and careful orchestration of multiple services. You can obtain the SageMaker Unified Studio URL for your domains by accessing the AWS Management Console for Amazon DataZone.

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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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AWS Machine Learning Blog

JANUARY 26, 2023

Since March 2014, Best Egg has delivered $22 billion in consumer personal loans with strong credit performance, welcomed almost 637,000 members to the recently launched Best Egg Financial Health platform, and empowered over 180,000 cardmembers who carry the new Best Egg Credit Card in their wallet. ML insights facilitate decision-making.

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AWS Machine Learning Blog

JUNE 24, 2024

Amazon SageMaker Ground Truth is an AWS managed service that makes it straightforward and cost-effective to get high-quality labeled data for machine learning (ML) models by combining ML and expert human annotation. Their web application is developed using AWS Amplify. Krikey’s AI tools are available online at www.krikey.ai

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Snorkel AI

MAY 24, 2023

Our speakers lead their fields and embody the desire to create revolutionary ML experiences by leveraging the power of data-centric AI to drive innovation and progress. Gideon Mann is the head of the ML Product and Research team in the Office of the CTO at Bloomberg LP. He is also the creator of Apache Spark.

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Snorkel AI

MAY 24, 2023

Our speakers lead their fields and embody the desire to create revolutionary ML experiences by leveraging the power of data-centric AI to drive innovation and progress. Gideon Mann is the head of the ML Product and Research team in the Office of the CTO at Bloomberg LP. He is also the creator of Apache Spark.

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Flipboard

JANUARY 15, 2025

The AWS global backbone network is the critical foundation enabling reliable and secure service delivery across AWS Regions. Specifically, we need to predict how changes to one part of the AWS global backbone network might affect traffic patterns and performance across the entire system.

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AWS Machine Learning Blog

MAY 24, 2023

JumpStart provides pretrained, open-source models for a wide range of problem types to help you get started with machine learning (ML). JumpStart also provides solution templates that set up infrastructure for common use cases, and executable example notebooks for ML with Amazon SageMaker. Perform real-time batch inference.

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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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