Tag: Machine Learning

We are excited to highlight 125 AWS Partners that received new designations in November for our global AWS Competency, AWS Managed Service Provider (MSP), AWS Service Delivery, and AWS Service Ready programs. These designations span workload, solution, and industry, and help AWS customers identify top AWS Partners that can deliver on core business objectives. AWS Partners are focused on your success, helping customers take full advantage of the business benefits AWS has to offer.

Learn about the AWS AI services stack for government agencies and partners to develop intelligent automation solutions to extract information from digitalized paper documents. Intelligent Document Processing (IDP) is a solution that enables extraction and processing of specific data elements from documents using AI and machine learning techniques. AWS services that add AI/ML intelligence to IDP solutions include Amazon Textract, Amazon Comprehend, Amazon Augmented AI, and Amazon Kendra.

We are excited to introduce AI for data analytics (AIDA) partner solutions which embed predictive analytics into mainstream analytics workspaces. These AI/ML solutions from AWS Partners have interfaces and integrations that help bring predictive analytics into the normal workflow of business experts. AWS AIDA includes partner solutions from Amplitude, Anaplan, Causality Link, Domo, Exasol, InterWorks, Pegasystems, Provectus, Qlik, Snowflake, Tableau, TIBCO, and Workato.

Enterprise data warehouses are complex and consist of database objects that need to be modified to reflect the changing needs of business, data analytics, and machine learning teams. In this post, learn about an approach to managing the evolution of enterprise-scale data warehouses based on the experience of Deloitte’s Data and AI global practice teams. The declarative tool developed by Deloitte that can automatically generate DDL statements to align Amazon Redshift’s state to an approved baseline configuration.

Dataiku orchestrates the entire machine learning lifecycle and makes it accessible to data scientists and analysts alike. With deep integration with AWS AI tools, Dataiku enables users to augment their analytics workflow with pretrained NLP and computer vision models. Learn how you can use Amazon Comprehend and Amazon Rekognition plugins on Dataiku Data Science Studio (DSS) to build a simple workflow of NLP and computer vision use cases, respectively.

Building effective machine learning models requires storing and managing historical data, but conventional databases can quickly become a nightmare to regulate. Queries start taking too long, for example, slowing down business decisions. Learn how to use Amazon Redshift ML and Query Editor V2 to create, train, and apply ML models to predict diabetes cases for a sample diabetes dataset. You can follow a similar approach to address other use cases such as customer churn prediction and fraud detection.

We are excited to highlight 88 AWS Partners that received new designations in October for our global AWS Competency, AWS Managed Service Provider (MSP), AWS Service Delivery, and AWS Service Ready programs. These designations span workload, solution, and industry, and help AWS customers identify top AWS Partners that can deliver on core business objectives. AWS Partners are focused on your success, helping customers take full advantage of the business benefits AWS has to offer.

By avoiding inspections, insurers lose the opportunity to adequately consider all factors during underwriting and take on more risk. TCS has built a virtual inspection solution on AWS that is customizable to various inspection use cases, such as home insurance inspections and claims, auto claims damage assessment and estimation, and mortgage inspection. This post provides an overview of the TCS virtual inspection solution, describes the high-level architecture, and explores the potential business benefits for insurers.

As multi-tenant SaaS providers look to leverage machine learning services, they must consider how they’ll protect the data that flows in and out of these services from different tenants. Learn how tenant isolation of machine learning services can be achieved using AWS IAM, and how the integration between IAM, Amazon SageMaker, and many other AWS services provide developers with a rich set of mechanisms that can be applied to realize tenant isolation goals.

Operationalizing machine learning models can be a challenge due to lack of established ML architecture and its integration with the existing landscape. DataRobot integrates with AWS and provides the flexibility for a model trained in DataRobot to be deployed on AWS services with centralized model governance, management, and monitoring. Learn how the DataRobot AutoML platform orchestrates the complete model development and training lifecycle.