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Improving air quality with generative AI

AWS Machine Learning Blog

The solution harnesses the capabilities of generative AI, specifically Large Language Models (LLMs), to address the challenges posed by diverse sensor data and automatically generate Python functions based on various data formats. This allows for data to be aggregated for further manufacturer-agnostic analysis.

AWS 132
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How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action

Flipboard

This use case highlights how large language models (LLMs) are able to become a translator between human languages (English, Spanish, Arabic, and more) and machine interpretable languages (Python, Java, Scala, SQL, and so on) along with sophisticated internal reasoning.

Database 158
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The NLP Cypher | 02.14.21

Towards AI

Their infrastructure is built on top of FastAPI and supports Python, Go and Ruby languages. which features a nice tutorial for you to get familiar with their library: Contextualized Topic Modeling with Python (EACL2021) In this blog post, I discuss our latest published paper on topic modeling: fbvinid.medium.com Colab of the Week ?

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Share medical image research on Amazon SageMaker Studio Lab for free

Flipboard

With these installation steps, you have successfully installed the medical-image-ai Python kernel and the ImJoy extension as the prerequisite to run the TCIA notebooks together with itkWidgets on Studio Lab. Make sure to choose the medical-image-ai Python kernel when running the TCIA notebooks in Studio Lab.

AWS 132
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Boosting RAG-based intelligent document assistants using entity extraction, SQL querying, and agents with Amazon Bedrock

AWS Machine Learning Blog

Overview of RAG RAG solutions are inspired by representation learning and semantic search ideas that have been gradually adopted in ranking problems (for example, recommendation and search) and natural language processing (NLP) tasks since 2010. We use the following Python script to recreate tables as pandas DataFrames.

SQL 126
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A single letter can direct our perception

Dataconomy

in 2010 , found that camel case identifiers led to higher accuracy and lower visual effort when compared to snake case identifiers. Snake case is commonly used in programming languages like Python and Ruby. It is also used for database table and column names in some operating systems. For example, a 2009 study by Binkley et al.

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The NLP Cypher | 02.14.21

Towards AI

Their infrastructure is built on top of FastAPI and supports Python, Go and Ruby languages. which features a nice tutorial for you to get familiar with their library: Contextualized Topic Modeling with Python (EACL2021) In this blog post, I discuss our latest published paper on topic modeling: fbvinid.medium.com Colab of the Week ?