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Store Sales Forecasting with Snowflake Cortex ML & Snowpark

phData

The brand-new Forecasting tool created on Snowflake Data Cloud Cortex ML allows you to do just that. What is Cortex ML, and Why Does it Matter? Cortex ML is Snowflake’s newest feature, added to enhance the ease of use and low-code functionality of your business’s machine learning needs.

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Reinventing the data experience: Use generative AI and modern data architecture to unlock insights

AWS Machine Learning Blog

The combination of large language models (LLMs), including the ease of integration that Amazon Bedrock offers, and a scalable, domain-oriented data infrastructure positions this as an intelligent method of tapping into the abundant information held in various analytics databases and data lakes.

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Create a multimodal chatbot tailored to your unique dataset with Amazon Bedrock FMs

AWS Machine Learning Blog

Solution overview For our custom multimodal chat assistant, we start by creating a vector database of relevant text documents that will be used to answer user queries. This script can be acquired directly from Amazon S3 using aws s3 cp s3://aws-blogs-artifacts-public/artifacts/ML-16363/deploy.sh. us-east-1 or bash deploy.sh

AWS 118
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Your guide to generative AI and ML at AWS re:Invent 2023

AWS Machine Learning Blog

Now all you need is some guidance on generative AI and machine learning (ML) sessions to attend at this twelfth edition of re:Invent. In addition to several exciting announcements during keynotes, most of the sessions in our track will feature generative AI in one form or another, so we can truly call our track “Generative AI and ML.”

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Use a generative AI foundation model for summarization and question answering using your own data

Flipboard

We create embeddings for each segment and store them in the open-source Chroma vector database via langchain’s interface. We save the database in an Amazon Elastic File System (Amazon EFS) file system for later use. In entered the Big Data space in 2013 and continues to explore that area. text.strip().replace('n',

AWS 79
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Monitor embedding drift for LLMs deployed from Amazon SageMaker JumpStart

AWS Machine Learning Blog

In this pattern, the recipe text is converted into embedding vectors using an embedding model, and stored in a vector database. Incoming questions are converted to embeddings, and then the vector database runs a similarity search to find related content. In entered the Big Data space in 2013 and continues to explore that area.

AWS 108
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Accelerate time to business insights with the Amazon SageMaker Data Wrangler direct connection to Snowflake

AWS Machine Learning Blog

Amazon SageMaker Data Wrangler is a single visual interface that reduces the time required to prepare data and perform feature engineering from weeks to minutes with the ability to select and clean data, create features, and automate data preparation in machine learning (ML) workflows without writing any code.

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