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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AWS Machine Learning Blog

SEPTEMBER 27, 2024

We can also gain an understanding of data presented in charts and graphs by asking questions related to business intelligence (BI) tasks, such as “What is the sales trend for 2023 for company A in the enterprise market?” AWS Fargate is the compute engine for web application. This allows you to experiment quickly with new designs.

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AWS Machine Learning Blog

AUGUST 26, 2024

At AWS, we are transforming our seller and customer journeys by using generative artificial intelligence (AI) across the sales lifecycle. It will be able to answer questions, generate content, and facilitate bidirectional interactions, all while continuously using internal AWS and external data to deliver timely, personalized insights.

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AWS Machine Learning Blog

NOVEMBER 29, 2023

Since launching in June 2023, the AWS Generative AI Innovation Center team of strategists, data scientists, machine learning (ML) engineers, and solutions architects have worked with hundreds of customers worldwide, and helped them ideate, prioritize, and build bespoke solutions that harness the power of generative AI.

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AWS Machine Learning Blog

AUGUST 28, 2023

As part of the 2023 Data Science Conference (DSCO 23), AWS partnered with the Data Institute at the University of San Francisco (USF) to conduct a datathon. During the datathon, my team member and I conducted research on different ML models (LightGBM, logistic regression, SVM models, Random Forest Classifier, etc.)

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Dataconomy

FEBRUARY 6, 2024

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. Why does AI/ML deserve to be the future of the modern world? Let’s understand the crucial role of AI/ML in the tech industry.

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AWS Machine Learning Blog

OCTOBER 22, 2024

Amazon SageMaker is a cloud-based machine learning (ML) platform within the AWS ecosystem that offers developers a seamless and convenient way to build, train, and deploy ML models. In 2023, SageMaker announced the release of the new SageMaker Studio, which offers two new types of applications: JupyterLab and Code Editor.

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Towards AI

AUGUST 18, 2023

Last Updated on August 19, 2023 by Editorial Team Author(s): Paul Iusztin Originally published on Towards AI. Terraform 101: How to Use Terraform as an MLE to Automate a Production-Ready AWS Infrastructure This member-only story is on us. Upgrade to access all of Medium. without making even one manual click!

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AWS Machine Learning Blog

SEPTEMBER 19, 2023

Amazon SageMaker Feature Store provides an end-to-end solution to automate feature engineering for machine learning (ML). For many ML use cases, raw data like log files, sensor readings, or transaction records need to be transformed into meaningful features that are optimized for model training. 2023| New| NA|36895.00|36895|

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IBM Journey to AI blog

MARCH 14, 2024

The solution: IBM databases on AWS To solve for these challenges, IBM’s portfolio of SaaS database solutions on Amazon Web Services (AWS), enables enterprises to scale applications, analytics and AI across the hybrid cloud landscape. Let’s delve into the database portfolio from IBM available on AWS. 

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Towards AI

OCTOBER 4, 2023

Last Updated on October 6, 2023 by Editorial Team Author(s): ????Mike Advanced-Data Engineering and ML Ops with Infrastructure as Code This member-only story is on us. This article is for data and ML Ops engineers who would want to deploy and update ML pipelines using CloudFormation templates.

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AWS Machine Learning Blog

MAY 23, 2023

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

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AWS Machine Learning Blog

NOVEMBER 15, 2023

In this post, we demonstrate how data aggregated within the AWS CCI Post Call Analytics solution allowed Principal to gain visibility into their contact center interactions, better understand the customer journey, and improve the overall experience between contact channels while also maintaining data integrity and security.

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AWS Machine Learning Blog

FEBRUARY 6, 2024

QnABot on AWS is an open source solution built using AWS native services like Amazon Lex , Amazon OpenSearch Service , AWS Lambda , Amazon Transcribe , and Amazon Polly. According to Gartner Magic Quadrant 2023, ServiceNow is one of the leading IT Service Management (ITSM) providers on the market. QnABot version 5.4+

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ODSC - Open Data Science

AUGUST 3, 2023

ML for Big Data with PySpark on AWS, Asynchronous Programming in Python, and the Top Industries for AI Harnessing Machine Learning on Big Data with PySpark on AWS In this brief tutorial, you’ll learn some basics on how to use Spark on AWS for machine learning, MLlib, and more. Check them out here.

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AWS Machine Learning Blog

MAY 14, 2024

RLHF is a technique that combines rewards and comparisons, with human feedback to pre-train or fine-tune a machine learning (ML) model. We present the solution and provide an example by simulating a case where the tier one AWS experts are notified to help customers using a chat-bot.

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The MLOps Blog

JUNE 27, 2023

As you delve into the landscape of MLOps in 2023, you will find a plethora of tools and platforms that have gained traction and are shaping the way models are developed, deployed, and monitored. For example, if you use AWS, you may prefer Amazon SageMaker as an MLOps platform that integrates with other AWS services.

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IBM Journey to AI blog

MAY 26, 2023

The role of AWS and cloud security in life sciences However, with greater power comes great responsibility. Most life sciences companies are raising their security posture with AWS infrastructure and services. Organizations like Moderna and Bristol Myers Squibb have chosen AWS to run their regulated workloads.

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Towards AI

JUNE 24, 2023

Last Updated on June 28, 2023 by Editorial Team Author(s): Anirudh Mehta Originally published on Towards AI. The ’31 Questions that Shape Fortune 500 ML Strategy’ highlighted key questions to assess the maturity of an ML system. A robust ML platform offers managed solutions to easily address these aspects.

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Towards AI

APRIL 4, 2023

Last Updated on April 4, 2023 by Editorial Team Introducing a Python SDK that allows enterprises to effortlessly optimize their ML models for edge devices. With their groundbreaking web-based Studio platform, engineers have been able to collect data, develop and tune ML models, and deploy them to devices.

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AWS Machine Learning Blog

APRIL 10, 2023

You don’t have to be an expert in machine learning (ML) to appreciate the value of large language models (LLMs). ML practitioners keep improving the accuracy and capabilities of these models. In this post, we take the same approach but host the model on AWS Inferentia2. This is particularly useful for large language models.

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AWS Machine Learning Blog

OCTOBER 29, 2024

This engine uses artificial intelligence (AI) and machine learning (ML) services and generative AI on AWS to extract transcripts, produce a summary, and provide a sentiment for the call. Organizations typically can’t predict their call patterns, so the solution relies on AWS serverless services to scale during busy times.

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AWS Machine Learning Blog

JULY 26, 2023

Generative AI Foundations on AWS is a new technical deep dive course that gives you the conceptual fundamentals, practical advice, and hands-on guidance to pre-train, fine-tune, and deploy state-of-the-art foundation models on AWS and beyond. Feel free to reach out to me on Medium, LinkedIn , GitHub , or through your AWS teams.

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AWS Machine Learning Blog

NOVEMBER 21, 2024

The integrated approach and ease of use of Amazon Bedrock in deploying large language models (LLMs), along with built-in features that facilitate seamless integration with other AWS services like Amazon Kendra, made it the preferred choice. This workflow integrates AWS services to extract, process, and make content available for querying.

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AWS Machine Learning Blog

APRIL 20, 2023

Each machine learning (ML) system has a unique service level agreement (SLA) requirement with respect to latency, throughput, and cost metrics. Based on Inference Recommender’s instance type recommendations, we can find the right real-time serving ML instances that yield the right price-performance for this use case.

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AWS Machine Learning Blog

OCTOBER 16, 2024

Amazon SageMaker supports geospatial machine learning (ML) capabilities, allowing data scientists and ML engineers to build, train, and deploy ML models using geospatial data. We pick the first week of December 2023 in this example. This way, our analysis is based on clear and reliable imagery.

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AWS Machine Learning Blog

MAY 7, 2024

Based on a survey conducted by American Express in 2023, 41% of business meetings are expected to take place in hybrid or virtual format by 2024. Hugging Face is an open-source machine learning (ML) platform that provides tools and resources for the development of AI projects.

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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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Flipboard

NOVEMBER 28, 2023

In 2023, the pace of adoption of AI technologies has accelerated further with the development of powerful foundation models (FMs) and a resulting advancement in generative AI capabilities. She also helps internal teams and AWS customers get started on their responsible AI journey. In this post, we focus on AI system risk, primarily.

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AWS Machine Learning Blog

NOVEMBER 18, 2024

To address this challenge, this post demonstrates a proactive approach for security vulnerability assessment of your accounts and workloads, using Amazon GuardDuty , Amazon Bedrock , and other AWS serverless technologies. This form of automation can help improve efficiency and reduce the response time to security threats.

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Flipboard

NOVEMBER 20, 2023

In SageMaker Studio, the integrated development environment (IDE) purpose-built for ML, you can launch notebooks that run on different instance types and with different configurations, collaborate with colleagues, and access additional purpose-built features for machine learning (ML). embeddings.

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AWS Machine Learning Blog

NOVEMBER 6, 2024

Amazon Transcribe is a machine learning (ML) based managed service that automatically converts speech to text, enabling developers to seamlessly integrate speech-to-text capabilities into their applications. Transcribe audio with Amazon Transcribe In this case, we use an AWS re:Invent 2023 technical talk as a sample.

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AWS Machine Learning Blog

JULY 24, 2023

In this post we walk you through the process of deploying FastAPI model servers on AWS Inferentia devices (found on Amazon EC2 Inf1 and Amazon EC Inf2 instances). Each AWS Inferentia1 device contains four NeuronCores-v1 and each AWS Inferentia2 device contains two NeuronCores-v2. For example, NEURON_RT_NUM_CORES=2 myapp.py

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AWS Machine Learning Blog

OCTOBER 17, 2024

Amazon Transcribe uses advanced speech recognition algorithms and machine learning (ML) models to accurately partition speakers and transcribe the audio, handling various accents, background noise, and other challenges. Deployment, as described below, is currently supported only in the US West (Oregon) us-west-2 AWS Region.

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Mlearning.ai

DECEMBER 22, 2023

You can jump AWS authentication steps if you're already in AWS 's environment. Harwarde requirements We ran an experiment ran in the ml.g5.24xlarge AWS instance which contains 8x A10g GPUs with a proprietary curated instructions dataset with domain-specific applications. 1.46k [00:00<? . 1.46k [00:00<?, ?B/s]

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ODSC - Open Data Science

FEBRUARY 2, 2023

The role of a data scientist is in demand and 2023 will be no exception. To get a better grip on those changes we reviewed over 25,000 data scientist job descriptions from that past year to find out what employers are looking for in 2023. However, each year the skills and certainly the platforms change somewhat.

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ODSC - Open Data Science

MARCH 27, 2023

Learn about the flow, difficulties, and tools for performing ML clustering at scale Ori Nakar | Principal Engineer, Threat Research | Imperva Given that there are billions of daily botnet attacks from millions of different IPs, the most difficult challenge of botnet detection is choosing the most relevant data.

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