Remove Categorization Remove Explainability Remove Information
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Generate training data and cost-effectively train categorical models with Amazon Bedrock

AWS Machine Learning Blog

In this post, we explore how you can use Amazon Bedrock to generate high-quality categorical ground truth data, which is crucial for training machine learning (ML) models in a cost-sensitive environment. For a multiclass classification problem such as support case root cause categorization, this challenge compounds many fold.

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AI for Universal Audio Understanding: Qwen-Audio Explained

AssemblyAI

  This problem is harder for audio because audio data is far more information-dense than text. A joint audio-language model trained on suitably expansive datasets of audio and text could learn more universal representations to transfer robustly across both modalities. 

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Can CatBoost with Cross-Validation Handle Student Engagement Data with Ease?

Towards AI

This story explores CatBoost, a powerful machine-learning algorithm that handles both categorical and numerical data easily. CatBoost is a powerful, gradient-boosting algorithm designed to handle categorical data effectively. CatBoost automatically transforms them, making it ideal for datasets with many categorical variables.

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The Role of Semantic Layers in Self-Service BI

Unite.AI

This, in turn, empowers business users with self-service business intelligence (BI), allowing them to make informed decisions without relying on IT teams. This article will explain what a semantic layer is, why businesses need one, and how it enables self-service business intelligence. The demand for self-service BI is growing quickly.

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Judicial systems are turning to AI to help manage its vast quantities of data and expedite case resolution

IBM Journey to AI blog

The Ministry of Justice in Baden-Württemberg recommended using AI with natural language understanding (NLU) and other capabilities to help categorize each case into the different case groups they were handling. Explainability will play a key role. The courts needed a transparent, traceable system that protected data.

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HARPA AI Review: How I Finally Tamed My Tab Overload

Unite.AI

Content creators like bloggers and social media managers can use HARPA AI to generate content ideas, optimize posts for SEO, and summarize information from various sources. E-commerce professionals can use HARPA AI to track prices and products across platforms to stay informed about market trends and competitor offerings.

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Effectively use prompt caching on Amazon Bedrock

AWS Machine Learning Blog

Dynamic content, including user-specific information, should be placed at the end of the prompt. How to use prompt caching When evaluating a use case to use prompt caching, its crucial to categorize the components of a given prompt into two distinct groups: the static and repetitive portion, and the dynamic portion. 2][3]'" "nn5.