article thumbnail

Automate document validation and fraud detection in the mortgage underwriting process using AWS AI services: Part 1

AWS Machine Learning Blog

In this three-part series, we present 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. Vinnie Saini is a Senior Solutions Architect at Amazon Web Services (AWS) based in Toronto, Canada.

AWS 69
article thumbnail

Navigating tomorrow: Role of AI and ML in information technology

Dataconomy

This popularity is primarily due to the spread of big data and advancements in algorithms. Going back from the times when AI was merely associated with futuristic visions to today’s reality, where ML algorithms seamlessly navigate our daily lives. These technologies have undergone a profound evolution. billion by 2032.

ML 121
professionals

Sign Up for our Newsletter

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

article thumbnail

Federated learning on AWS using FedML, Amazon EKS, and Amazon SageMaker

AWS Machine Learning Blog

To mitigate these risks, the FL model uses personalized training algorithms and effective masking and parameterization before sharing information with the training coordinator. Therefore, ML creates challenges for AWS customers who need to ensure privacy and security across distributed entities without compromising patient outcomes.

AWS 102
article thumbnail

Accelerate time to business insights with the Amazon SageMaker Data Wrangler direct connection to Snowflake

AWS Machine Learning Blog

This includes provisioning Amazon Simple Storage Service (Amazon S3) buckets, AWS Identity and Access Management (IAM) access permissions, Snowflake storage integration for individual users, and an ongoing mechanism to manage or clean up data copies in Amazon S3. An AWS account with admin access. Choose Add step.

ML 74
article thumbnail

Containerization of Machine Learning Applications

Heartbeat

However, the emergence of the open-source Docker engine by Solomon Hykes in 2013 accelerated the adoption of the technology. catboost is the machine learning algorithm for model building. The model can be improved with more comprehensive preprocessing, hyperparameter tuning, and algorithm choices. What is Docker? Flask==2.1.2

article thumbnail

How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action

Flipboard

In this post, we show you how SnapLogic , an AWS customer, used Amazon Bedrock to power their SnapGPT product through automated creation of these complex DSL artifacts from human language. SnapLogic background SnapLogic is an AWS customer on a mission to bring enterprise automation to the world.

Database 112