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Natural Language Processing & Machine Learning in Higher Education

Mentormate

In this article, we will discuss how MentorMate and our partner eLumen leveraged natural language processing (NLP) and machine learning (ML) for data-driven decision-making to tame the curriculum beast in higher education. Here, we will primarily focus on drawing insights from structured and unstructured (text) data.

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eSentire delivers private and secure generative AI interactions to customers with Amazon SageMaker

AWS Machine Learning - AI

To accomplish this, eSentire built AI Investigator, a natural language query tool for their customers to access security platform data by using AWS generative artificial intelligence (AI) capabilities. Therefore, eSentire decided to build their own LLM using Llama 1 and Llama 2 foundational models.

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Build a contextual text and image search engine for product recommendations using Amazon Bedrock and Amazon OpenSearch Serverless

AWS Machine Learning - AI

In this post, we show how to build a contextual text and image search engine for product recommendations using the Amazon Titan Multimodal Embeddings model , available in Amazon Bedrock , with Amazon OpenSearch Serverless. Amazon SageMaker Studio – It is an integrated development environment (IDE) for machine learning (ML).

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Streamline financial workflows with generative AI for email automation

AWS Machine Learning - AI

Intelligent automation presents a chance to revolutionize document workflows across sectors through digitization and process optimization. This post explains a generative artificial intelligence (AI) technique to extract insights from business emails and attachments. Data summarization using large language models (LLMs).

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Build a self-service digital assistant using Amazon Lex and Knowledge Bases for Amazon Bedrock

AWS Machine Learning - AI

Generative artificial intelligence (AI)-powered chatbots play a crucial role in delivering human-like interactions by providing responses from a knowledge base without the involvement of live agents. Select the embedding model to vectorize the documents. Create an Amazon Lex bot. Choose Next.

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Introducing guardrails in Knowledge Bases for Amazon Bedrock

AWS Machine Learning - AI

We recently announced the general availability of Guardrails for Amazon Bedrock , which allows you to implement safeguards in your generative artificial intelligence (AI) applications that are customized to your use cases and responsible AI policies. We store the dataset in an Amazon Simple Storage Service (Amazon S3) bucket.

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Leveraging Serverless and Generative AI for Image Captioning on GCP

Xebia

Leveraging Serverless and Generative AI for Image Captioning on GCP In today’s age of abundant data, especially visual data, it’s imperative to understand and categorize images efficiently. TL;DR We’ve built an automated, serverless system on Google Cloud Platform where: Users upload images to a Google Cloud Storage Bucket.