article thumbnail

Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models. Data science and DevOps teams may face challenges managing these isolated tool stacks and systems.

article thumbnail

Build an agronomic data platform with Amazon SageMaker geospatial capabilities

AWS Machine Learning

Data-driven decisions fueled by near-real-time insights can enable farmers to close the gap on increased food demand. However, scouting each field on a frequent basis for large fields and farms is not feasible, and successful risk mitigation requires an integrated agronomic data platform that can bring insights at scale.

APIs 74
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Accenture creates a regulatory document authoring solution using AWS generative AI services

AWS Machine Learning

Accenture built a regulatory document authoring solution using automated generative AI that enables researchers and testers to produce CTDs efficiently. By extracting key data from testing reports, the system uses Amazon SageMaker JumpStart and other AWS AI services to generate CTDs in the proper format.

article thumbnail

Build a secure enterprise application with Generative AI and RAG using Amazon SageMaker JumpStart

AWS Machine Learning

It’s powered by large language models (LLMs) that are pre-trained on vast amounts of data and commonly referred to as foundation models (FMs). These SageMaker endpoints are consumed in the Amplify React application through Amazon API Gateway and AWS Lambda functions. This dataset is a large corpus of legal and administrative data.

article thumbnail

Configure an AWS DeepRacer environment for training and log analysis using the AWS CDK

AWS Machine Learning

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. Navigate to the AWS Cloud9 console.

Scripts 74
article thumbnail

Automated exploratory data analysis and model operationalization framework with a human in the loop

AWS Machine Learning

Identifying, collecting, and transforming data is the foundation for machine learning (ML). According to a Forbes survey , there is widespread consensus among ML practitioners that data preparation accounts for approximately 80% of the time spent in developing a viable ML model. Overview of solution.

article thumbnail

Large-scale revenue forecasting at Bosch with Amazon Forecast and Amazon SageMaker custom models

AWS Machine Learning

Bosch is a multinational corporation with entities operating in multiple sectors, including automotive, industrial solutions, and consumer goods. Because neural forecasters are trained on historical data, the forecasts generated based on out-of-distribution data from the more volatile periods could be inaccurate and unreliable.

APIs 83