Remove section movies
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Personalize your generative AI applications with Amazon SageMaker Feature Store

AWS Machine Learning Blog

For instance, in an application that recommends movies, features could include previous ratings, preference categories, and demographics. Solution overview Let’s imagine a scenario where a movie entertainment company promotes movies to different users via an email campaign. A feature store maintains user profile data.

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From Static Slides to Smart Speeches: The Rise of AI-Powered Presentations

Unite.AI

Illustrative Examples: For example, you could prompt DALL-E to create an image of a couple holding hands while scuba diving among colorful tropical fish, similar to scenes from the Avatar movies. AI can even analyze your eye contact patterns, highlighting sections where you might be disengaged from the audience.

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Prepare your data for Amazon Personalize with Amazon SageMaker Data Wrangler

AWS Machine Learning Blog

In this post, we walk through how to prepare and import the MovieLens dataset , a dataset prepared by GroupLens research at the University of Minnesota, which consists of a variety of user rankings of various movies, into Amazon Personalize using Amazon SageMaker Data Wrangler. [1] We want to build a movie recommender engine based on that.

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How AI is Transforming IT Service Management

Unite.AI

The Evolution of AI in the Tech Industry Remember when AI was just a concept we marveled at in sci-fi movies? Let's look into these more closely in the following sections. Those days are long gone. Today, AI has transformed from a fantastical idea into a real-world solution.

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Turning data into gold: 10 exceptional AI marketing campaign examples

AI News

This section delves into the diverse ways AI can seamlessly integrate into marketing strategies for achieving optimal results. These algorithms analyze user behavior and preferences to recommend relevant movies, TV shows, and даже artwork that aligns with individual tastes.

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Knowledge Bases for Amazon Bedrock now supports metadata filtering to improve retrieval accuracy

AWS Machine Learning Blog

For example, you can use legal documents with similar terms for different contexts, or movies that have a similar plot released in different years. Solution overview In the following sections, we demonstrate how to prepare a dataset to use as a knowledge base, and then query with metadata filtering.

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Llamaindex Query Pipelines: Quickstart Guide to the Declarative Query API

Towards AI

We’ll cover some of these use cases in the following sections. try chaining basic promptsprompt_str = "Please generate related movies to {movie_name}"prompt_tmpl = PromptTemplate(prompt_str)llm = OpenAI(model="gpt-3.5-turbo")# look at summarizer input keysprint(summarizer.as_query_component().input_keys)

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