AWS Machine Learning Blog

APRIL 29, 2024

In 2024, however, organizations are using large language models (LLMs), which require relatively little focus on NLP, shifting research and development from modeling to the infrastructure needed to support LLM workflows. Metaflow’s coherent APIs simplify the process of building real-world ML/AI systems in teams.

AWS 132

AWS ML ML Python 132

AWS Machine Learning Blog

SEPTEMBER 18, 2024

The ZMP analyzes billions of structured and unstructured data points to predict consumer intent by using sophisticated artificial intelligence (AI) to personalize experiences at scale. Hosted on Amazon ECS with tasks run on Fargate, this platform streamlines the end-to-end ML workflow, from data ingestion to model deployment.

AWS 128

AWS Machine Learning Machine Learning ML 128

AWS Machine Learning Blog

SEPTEMBER 5, 2023

In order to improve our equipment reliability, we partnered with the Amazon Machine Learning Solutions Lab to develop a custom machine learning (ML) model capable of predicting equipment issues prior to failure. Our teams developed a framework for processing over 50 TB of historical sensor data and predicting faults with 91% precision.

AWS 129

AWS ML ML Machine Learning 129

AWS Machine Learning Blog

JULY 17, 2024

As a customer, you rely on Amazon Web Services (AWS) expertise to be available and understand your specific environment and operations. Amazon Q Business is a fully managed, secure, generative-AI powered enterprise chat assistant that enables natural language interactions with your organization’s data.

AWS 131

AWS AI AI Artificial Intelligence 131

AWS Machine Learning Blog

JANUARY 24, 2025

In this post, we delve into the essential security best practices that organizations should consider when fine-tuning generative AI models. Security in Amazon Bedrock Cloud security at AWS is the highest priority. Amazon Bedrock prioritizes security through a comprehensive approach to protect customer data and AI workloads.

AWS 121

AWS AI AI Machine Learning 121

AWS Machine Learning Blog

NOVEMBER 22, 2024

Using this approach, you can focus on developing and refining the model while using the fully managed training infrastructure provided by SageMaker Training. Implementation details We spin up the cluster by calling the SageMaker control plane through APIs or the AWS Command Line Interface (AWS CLI) or using the SageMaker AWS SDK.

Clustering 98

Clustering AWS ML ML 98

Hacker News

NOVEMBER 19, 2024

Here are a few of the things that you might do as an AI Engineer at TigerEye: - Design, develop, and validate statistical models to explain past behavior and to predict future behavior of our customers’ sales teams - Own training, integration, deployment, versioning, and monitoring of ML components - Improve TigerEye’s existing metrics collection and (..)

Computer Science 162

Computer Science Computer Science ML ML 162

AWS Machine Learning Blog

JANUARY 27, 2025

Amazon SageMake r provides a seamless experience for building, training, and deploying machine learning (ML) models at scale. For this post, we use the us-east-1 AWS Region: Have access to a POSIX based (Mac/Linux) system or SageMaker notebooks. This post uses CodeBuild and a Docker Dockerfile to build the extended container.

AWS 110

AWS Deep Learning Deep Learning Machine Learning 110

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 billion in Pythia.

AWS 131

AWS Machine Learning Machine Learning Deep Learning 131

AWS Machine Learning Blog

JUNE 22, 2023

Working with AWS, Light & Wonder recently developed an industry-first secure solution, Light & Wonder Connect (LnW Connect), to stream telemetry and machine health data from roughly half a million electronic gaming machines distributed across its casino customer base globally when LnW Connect reaches its full potential.

AWS 118

AWS ML ML Machine Learning 118

Data Science Dojo

OCTOBER 31, 2024

Growth Outlook: Companies like Google DeepMind, NASA’s Jet Propulsion Lab, and IBM Research actively seek research data scientists for their teams, with salaries typically ranging from $120,000 to $180,000. With the continuous growth in AI, demand for remote data science jobs is set to rise.

Data Science 195

Data Science Data Scientist Machine Learning Machine Learning 195

AWS Machine Learning Blog

APRIL 22, 2025

Haiku while still maintaining the baseline accuracy with the larger/ more expensive model (Sonnet 3.5 Getting started You can get started using the AWS Management Console for Amazon Bedrock. You can also use AWS Command Line Interface (AWS CLI) or API, to configure and use a prompt router.

AWS 117

AWS Machine Learning Machine Learning Deep Learning 117

AWS Machine Learning Blog

NOVEMBER 21, 2024

We guide you through deploying the necessary infrastructure using AWS CloudFormation , creating an internal labeling workforce, and setting up your first labeling job. This precision helps models learn the fine details that separate natural from artificial-sounding speech. We demonstrate how to use Wavesurfer.js

AWS 105

AWS AI AI Natural Language Processing 105

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. Add rules to interpret model scores. Deploy the API to make predictions.

ML 138

ML ML AWS Data Profiling 138

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.

Machine Learning 140

Machine Learning Machine Learning ML ML 140

AWS Machine Learning Blog

NOVEMBER 22, 2023

The AWS Well-Architected Framework provides a systematic way for organizations to learn operational and architectural best practices for designing and operating reliable, secure, efficient, cost-effective, and sustainable workloads in the cloud. These resources introduce common AWS services for IDP workloads and suggested workflows.

AWS 125

AWS ML ML Machine Learning 125

AWS Machine Learning Blog

AUGUST 21, 2023

Amazon SageMaker Data Wrangler reduces the time it takes to collect and prepare data for machine learning (ML) from weeks to minutes. Data is frequently kept in data lakes that can be managed by AWS Lake Formation , giving you the ability to implement fine-grained access control using a straightforward grant or revoke procedure.

AWS 98

AWS Data Lakes Clustering Data Preparation 98

AWS Machine Learning Blog

NOVEMBER 18, 2024

The key reasons that influenced this decision were: Managed service – Amazon Bedrock is a fully serverless offering that offers a choice of industry leading FMs without provisioning infrastructure, procuring GPUs around the clock, or configuring ML frameworks.

AI 115

AI AI Database AWS 115

AWS Machine Learning Blog

APRIL 25, 2024

We provide a comprehensive guide on how to deploy speaker segmentation and clustering solutions using SageMaker on the AWS Cloud. Solution overview Amazon Transcribe is the go-to service for speaker diarization in AWS. Hugging Face is a popular open source hub for machine learning (ML) models.

AWS 129

AWS ML ML Python 129

AWS Machine Learning Blog

JUNE 27, 2023

When machine learning (ML) models are deployed into production and employed to drive business decisions, the challenge often lies in the operation and management of multiple models. That is where Provectus , an AWS Premier Consulting Partner with competencies in Machine Learning, Data & Analytics, and DevOps, stepped in.

ML 123

ML ML AWS Machine Learning 123

O'Reilly Media

OCTOBER 19, 2021

As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. What does a modern technology stack for streamlined ML processes look like? Why: Data Makes It Different. All ML projects are software projects.

ML 145

ML ML Data Scientist AWS 145

AWS Machine Learning Blog

JULY 29, 2024

Amazon Forecast is a fully managed service that uses statistical and machine learning (ML) algorithms to deliver highly accurate time series forecasts. With SageMaker Canvas, you get faster model building , cost-effective predictions, advanced features such as a model leaderboard and algorithm selection, and enhanced transparency.

ML 124

ML ML Algorithm AWS 124

AWS Machine Learning Blog

MAY 4, 2023

Simple methods for time series forecasting use historical values of the same variable whose future values need to be predicted, whereas more complex, machine learning (ML)-based methods use additional information, such as the time series data of related variables. All of this is possible without having to write or compile code.

AWS 134

AWS ML ML Data Scientist 134

AWS Machine Learning Blog

SEPTEMBER 19, 2024

In this post, AWS collaborates with Meta’s PyTorch team to showcase how you can use Meta’s torchtune library to fine-tune Meta Llama-like architectures while using a fully-managed environment provided by Amazon SageMaker Training. SageMaker Training is a comprehensive, fully managed ML service that enables scalable model training.

AWS 101

AWS ML ML Machine Learning 101

AWS Machine Learning Blog

MAY 31, 2024

With the Amazon Bedrock serverless experience, you can get started quickly, privately customize FMs with your own data, and integrate and deploy them into your applications using the Amazon Web Services (AWS) tools without having to manage infrastructure. However, this is beyond the scope of this post.

AWS 136

AWS Machine Learning Machine Learning Database 136

ODSC - Open Data Science

OCTOBER 21, 2024

Fortunately, there are many tools for ML evaluation and frameworks designed to support responsible AI development and evaluation. But let’s first take a look at some of the tools for ML evaluation that are popular for responsible AI. It includes methods for addressing fairness issues by adjusting training data, models, or outputs.

ML 52

ML ML Machine Learning Machine Learning 52

AWS Machine Learning Blog

SEPTEMBER 12, 2024

Thomson Reuters , a global content and technology-driven company, has been using artificial intelligence and machine learning (AI/ML) in its professional information products for decades. LLMs disrupt the industry Towards the end of 2022, groundbreaking LLMs were released that realized drastic improvements over previous model capabilities.

Clustering 114

Clustering AWS ML ML 114

Towards AI

APRIL 28, 2025

Contents: Background Tests setup Results and Analysis Conclusion Background Volga is a data processing system built for modern AI/ML pipelines, with a focus on real-time feature engineering (read more here). Tests setup We ran load tests on an Amazon EKS cluster using t2.medium

Clustering 59

Clustering AWS ML ML 59

AWS Machine Learning Blog

NOVEMBER 15, 2023

AutoML allows you to derive rapid, general insights from your data right at the beginning of a machine learning (ML) project lifecycle. Understanding up front which preprocessing techniques and algorithm types provide best results reduces the time to develop, train, and deploy the right model.

Algorithm 126

Algorithm AWS ML ML 126

AWS Machine Learning Blog

NOVEMBER 10, 2023

Creating high-performance machine learning (ML) solutions relies on exploring and optimizing training parameters, also known as hyperparameters. It provides key functionality that allows you to focus on the ML problem at hand while automatically keeping track of the trials and results. We use a Random Forest from SkLearn.

ML 125

ML ML Algorithm Python 125

The MLOps Blog

JUNE 27, 2023

For example, if you use AWS, you may prefer Amazon SageMaker as an MLOps platform that integrates with other AWS services. Knowledge and skills in the organization Evaluate the level of expertise and experience of your ML team and choose a tool that matches their skill set and learning curve.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

AWS Machine Learning Blog

AUGUST 30, 2024

With the rapid growth of generative artificial intelligence (AI), many AWS customers are looking to take advantage of publicly available foundation models (FMs) and technologies. This includes Meta Llama 3, Meta’s publicly available large language model (LLM).

SQL 94

SQL AWS Database AI 94

DagsHub

AUGUST 29, 2024

Source: Author Introduction Machine learning (ML) models, like other software, are constantly changing and evolving. Version control systems (VCS) play a key role in this area by offering a structured method to track changes made to models and handle versions of data and code used in these ML projects.

ML 52

ML ML Python Machine Learning 52

The MLOps Blog

JANUARY 11, 2023

This can enable the company to leverage the data generated by its IoT edge devices to drive business decisions and gain a competitive advantage. AWS offers a three-layered machine learning stack to choose from based on your skill set and team’s requirements for implementing workloads to execute machine learning tasks.

AWS 52

AWS Machine Learning Machine Learning ML 52

Mlearning.ai

JUNE 7, 2023

AWS Inferentia accelerators are custom-built machine learning inference chips designed by Amazon Web Services (AWS) to optimize inference workloads on the AWS platform. The AWS Inferentia chips are designed with a focus on delivering high performance, low latency, and cost efficiency for inference workloads.

AWS 52

AWS Deep Learning Deep Learning AI 52

AWS Machine Learning Blog

JUNE 5, 2023

In this post, we show you how to train the 7-billion-parameter BloomZ model using just a single graphics processing unit (GPU) on Amazon SageMaker , Amazon’s machine learning (ML) platform for preparing, building, training, and deploying high-quality ML models. Then, it starts the training job.

AWS 103

AWS ML ML Machine Learning 103

Mlearning.ai

DECEMBER 22, 2023

You can jump AWS authentication steps if you're already in AWS 's environment. Tip: Only include libraries with the most updated version in the requirements.txt file, specially the transformerslibrary as it may miss newly updated models in older versions. You can find here more about it. 1.46k [00:00<?

AWS 52

AWS ML ML Python 52