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Streamline Sales Processes with Enterprise CPQ

Cincom

Managing sales processes across large organizations is complex. From coordinating teams to configuring quotes, enterprise companies face immense challenges keeping sales operations running smoothly. Centralized Pricing Management: Pricing data gets consolidated within CPQ. Related: What Is Configure Price Quote Software?

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

AWS Machine Learning

With the advent of these LLMs or FMs, customers can simply build Generative AI based applications for advertising, knowledge management, and customer support. You can use this post as a reference to build secure enterprise applications in the Generative AI domain using AWS services.

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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. Save model: This step creates a model from the trained model artifacts.

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

AWS Machine Learning

Using the job ID and message ID returned by the previous request, the client connects to the WebSocket API and sends the job ID and message ID to the WebSocket connection. A Lambda function invokes the Amazon Textract API DetectDocument to parse tabular data from source documents and stores extracted data into DynamoDB.

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

AWS Machine Learning

According to Accenture , companies that manage to efficiently scale AI and ML can achieve nearly triple the return on their investments. With the advancements in automation and configuring with increasing levels of abstraction to set up different environments with IaC tools, the AWS CDK is being widely adopted across various enterprises.

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

AWS Machine Learning

A Studio domain managed policy attached to the AWS Identity and Access Management (IAM) execution role. For instructions on assigning permissions to the role, refer to Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference. Prerequisites. The following figure illustrates our Step Function workflow.

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Bring SageMaker Autopilot into your MLOps processes using a custom SageMaker Project

AWS Machine Learning

Amazon SageMaker is a fully managed service to prepare data and build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows. For more information, refer to MLOps foundation roadmap for enterprises with Amazon SageMaker.