Analytics Vidhya

JULY 31, 2023

In an exciting collaboration, Amazon Web Services (AWS) and Accel have unveiled “ML Elevate 2023,” a revolutionary six-week accelerator program aimed at empowering startups in the generative artificial intelligence (AI) domain.

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Analytics Vidhya

NOVEMBER 1, 2021

Image 1- [link] Whether you are an experienced or an aspiring data scientist, you must have worked on machine learning model development comprising of data cleaning, wrangling, comparing different ML models, training the models on Python Notebooks like Jupyter. All the […].

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Flipboard

JULY 5, 2023

Today, we are delighted to introduce the latest version of the AWS Well-Architected Machine Learning (ML) Lens whitepaper. The AWS Well-Architected Framework provides architectural best practices for designing and operating ML workloads on AWS.

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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

DECEMBER 19, 2023

Artificial intelligence (AI) and machine learning (ML) are becoming an integral part of systems and processes, enabling decisions in real time, thereby driving top and bottom-line improvements across organizations. However, putting an ML model into production at scale is challenging and requires a set of best practices.

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KDnuggets

NOVEMBER 18, 2021

This is the guide on how to build a serverless data pipeline on AWS with a Machine Learning model deployed as a Sagemaker endpoint.

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AWS Machine Learning Blog

APRIL 16, 2024

At AWS, our top priority is safeguarding the security and confidentiality of our customers’ workloads. With the AWS Nitro System , we delivered a first-of-its-kind innovation on behalf of our customers. The Nitro System is an unparalleled computing backbone for AWS, with security and performance at its core.

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Flipboard

NOVEMBER 26, 2023

Today we are announcing two new optimized integrations for AWS Step Functions with Amazon Bedrock. Step Functions is a visual workflow service that helps developers build distributed applications, automate processes, orchestrate microservices, and create data and machine learning (ML) pipelines.

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AWS Machine Learning Blog

FEBRUARY 27, 2024

In this post, we share how Axfood, a large Swedish food retailer, improved operations and scalability of their existing artificial intelligence (AI) and machine learning (ML) operations by prototyping in close collaboration with AWS experts and using Amazon SageMaker.

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Flipboard

JULY 4, 2023

While there are some big names in the technology world that are worried about a potential existential threat posed by artificial intelligence (AI), Matt Wood, VP of product at AWS, is not one of them. Wood has long been a standard bearer for machine learning (ML) at AWS and is a fixture at the …

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Towards AI

OCTOBER 4, 2023

Advanced-Data Engineering and ML Ops with Infrastructure as Code This member-only story is on us. Photo by Markus Winkler on Unsplash This story explains how to create and orchestrate machine learning pipelines with AWS Step Functions and deploy them using Infrastructure as Code. Upgrade to access all of Medium.

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Flipboard

JUNE 20, 2023

Machine learning (ML) engineers have traditionally focused on striking a balance between model training and deployment cost vs. performance. This is important because training ML models and then using the trained models to make predictions (inference) can be highly energy-intensive tasks.

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AWS Machine Learning Blog

JANUARY 13, 2023

In this post, we show you how Parsons is building its next generation workforce by using machine learning (ML) and artificial intelligence (AI) with AWS DeepRacer in a fun and collaborative way. Parsons is on a mission to make AI/ML a foundation of business across the company.

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AWS Machine Learning Blog

OCTOBER 26, 2023

Intuitivo, a pioneer in retail innovation, is revolutionizing shopping with its cloud-based AI and machine learning (AI/ML) transactional processing system. Our solution outpaces traditional vending machines and alternatives, offering an economical edge with its ten times cheaper cost, easy setup, and maintenance-free operation.

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Flipboard

NOVEMBER 21, 2023

MATLAB   is a popular programming tool for a wide range of applications, such as data processing, parallel computing, automation, simulation, machine learning, and artificial intelligence. In recent years, MathWorks has brought many product offerings into the cloud, especially on Amazon Web Services (AWS).

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IBM Data Science in Practice

APRIL 4, 2023

Introduction This article shows how to monitor a model deployed on AWS Sagemaker for quality, bias and explainability, using IBM Watson OpenScale on the IBM Cloud Pak for Data platform. This article shows how to use the endpoint generated from that tutorial to demonstrate how to monitor the AWS deployment with Watson OpenScale.

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AWS Machine Learning Blog

JANUARY 5, 2024

This post was written in collaboration with Bhajandeep Singh and Ajay Vishwakarma from Wipro’s AWS AI/ML Practice. Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models.

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Flipboard

JUNE 26, 2023

These techniques utilize various machine learning (ML) based approaches. Overview of solution In this post, we go through the various steps to apply ML-based fuzzy matching to harmonize customer data across two different datasets for auto and property insurance. Run the AWS Glue ML transform job.

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Dataconomy

FEBRUARY 6, 2024

Artificial intelligence and machine learning are no longer the elements of science fiction; they’re the realities of today. With the ability to analyze a vast amount of data in real-time, identify patterns, and detect anomalies, AI/ML-powered tools are enhancing the operational efficiency of businesses in the IT sector.

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AWS Machine Learning Blog

APRIL 29, 2024

Close collaboration with AWS Trainium has also played a major role in making the Arcee platform extremely performant, not only accelerating model training but also reducing overall costs and enforcing compliance and data integrity in the secure AWS environment. Our cluster consisted of 16 nodes, each equipped with a trn1n.32xlarge

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Analytics Vidhya

NOVEMBER 26, 2020

Introduction: Gone are the days when enterprises set up their own in-house server and spending a gigantic amount of budget on storage infrastructure & The post Deployment of ML models in Cloud – AWS SageMaker?(in-built in-built algorithms) appeared first on Analytics Vidhya.

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IBM Data Science in Practice

MARCH 8, 2023

Introduction This article shows how to build a machine learning model on a Watson Studio platform running on IBM Cloud Pak for Data (CPD). You can then export the model and deploy it on Amazon Sagemaker on Amazon Web Server (AWS). SageMaker also enables developers to deploy ML models on embedded systems and edge-devices.

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AWS Machine Learning Blog

MARCH 30, 2023

Bundesliga and AWS have collaborated to perform an in-depth examination to study the quantification of achievements of Bundesliga’s keepers. The result is a machine learning (ML)-powered insight that allows fans to easily evaluate and compare the goalkeepers’ proficiencies. would be saved 9 out of 10 times.

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AWS Machine Learning Blog

FEBRUARY 26, 2024

By using AWS services, our architecture provides real-time visibility into LLM behavior and enables teams to quickly identify and address any issues or anomalies. In this post, we demonstrate a few metrics for online LLM monitoring and their respective architecture for scale using AWS services such as Amazon CloudWatch and AWS Lambda.

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Mlearning.ai

FEBRUARY 2, 2023

How I cleared AWS Machine Learning Specialty with three weeks of preparation (I will burst some myths of the online exam) How I prepared for the test, my emotional journey during preparation, and my actual exam experience Certified AWS ML Specialty Badge source Introduction:- I recently gave and cleared AWS ML certification on 29th Dec 2022.

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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. AWS Step Functions automatically initiate and monitor these workflows by simplifying error handling.

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AWS Machine Learning Blog

OCTOBER 30, 2023

Amazon Bedrock is a fully managed service provided by AWS that offers developers access to foundation models (FMs) and the tools to customize them for specific applications. The workflow steps are as follows: AWS Lambda running in your private VPC subnet receives the prompt request from the generative AI application.

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AWS Machine Learning Blog

MAY 10, 2023

Amazon SageMaker provides a broad selection of machine learning (ML) infrastructure and model deployment options to help meet your ML inference needs. New generations of CPUs offer a significant performance improvement in ML inference due to specialized built-in instructions. 4xlarge instances. 4xlarge instances.

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Towards AI

NOVEMBER 5, 2023

Source: [link] This article describes a solution for a generative AI resume screener that got us 3rd place at DataRobot & AWS Hackathon 2023. You can also set the environment variables on the notebook instance for things like AWS access key etc. Source: author’s screenshot on AWS We used Anthropic Claude 2 in our solution.

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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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Mlearning.ai

JANUARY 28, 2023

From Sale Marketing Business 7 Powerful Python ML For Data Science And Machine Learning need to be use. This post will outline seven powerful python ml libraries that can help you in data science and different python ml environment. Seven Python Libraries for Data Science and Machine Learning : 1.

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AWS Machine Learning Blog

MARCH 30, 2023

In this post, we introduce a new interactive tool called Snapper, powered by a machine learning (ML) model that reduces the effort required of annotators. ML model optimized for annotators A tremendous number of high-performing object detection models have been proposed by the computer vision community in recent years.

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AWS Machine Learning Blog

DECEMBER 12, 2023

In this post, we’ll summarize training procedure of GPT NeoX on AWS Trainium , a purpose-built machine learning (ML) accelerator optimized for deep learning training. M tokens/$) trained such models with AWS Trainium without losing any model quality. We’ll outline how we cost-effectively (3.2 2048 256 10.4

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AWS Machine Learning Blog

NOVEMBER 29, 2023

Data preparation is a crucial step in any machine learning (ML) workflow, yet it often involves tedious and time-consuming tasks. You’ll also see faster performance for transforms and analyses, and a natural language interface to explore and transform data for ML.

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AWS Machine Learning Blog

FEBRUARY 13, 2023

With the increasing use of artificial intelligence (AI) and machine learning (ML) for a vast majority of industries (ranging from healthcare to insurance, from manufacturing to marketing), the primary focus shifts to efficiency when building and training models at scale.

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AWS Machine Learning Blog

SEPTEMBER 20, 2023

For example, you might have acquired a company that was already running on a different cloud provider, or you may have a workload that generates value from unique capabilities provided by AWS. We show how you can build and train an ML model in AWS and deploy the model in another platform.

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AWS Machine Learning Blog

FEBRUARY 21, 2023

We’re thrilled to announce an expanded collaboration between AWS and Hugging Face to accelerate the training, fine-tuning, and deployment of large language and vision models used to create generative AI applications. AWS has a deep history of innovation in generative AI. Or they can self-manage on Amazon EC2.

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