Remove 2008 Remove Clustering Remove Natural Language Processing
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Zero-shot prompting for the Flan-T5 foundation model in Amazon SageMaker JumpStart

AWS Machine Learning Blog

We also demonstrate how you can engineer prompts for Flan-T5 models to perform various natural language processing (NLP) tasks. Task Prompt (template in bold) Model output Summarization Briefly summarize this paragraph: Amazon Comprehend uses natural language processing (NLP) to extract insights about the content of documents.

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A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

PBAs, such as graphics processing units (GPUs), have an important role to play in both these phases. The following figure illustrates the idea of a large cluster of GPUs being used for learning, followed by a smaller number for inference. With Inf1, they were able to reduce their inference latency by 25%, and costs by 65%.

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Identifying defense coverage schemes in NFL’s Next Gen Stats

AWS Machine Learning Blog

As an example, in the following figure, we separate Cover 3 Zone (green cluster on the left) and Cover 1 Man (blue cluster in the middle). We design an algorithm that automatically identifies the ambiguity between these two classes as the overlapping region of the clusters. Van der Maaten, Laurens, and Geoffrey Hinton.

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Financial text generation using a domain-adapted fine-tuned large language model in Amazon SageMaker JumpStart

AWS Machine Learning Blog

Large language models (LLMs) with billions of parameters are currently at the forefront of natural language processing (NLP). These models are shaking up the field with their incredible abilities to generate text, analyze sentiment, translate languages, and much more.

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Domain-adaptation Fine-tuning of Foundation Models in Amazon SageMaker JumpStart on Financial data

AWS Machine Learning Blog

Large language models (LLMs) with billions of parameters are currently at the forefront of natural language processing (NLP). These models are shaking up the field with their incredible abilities to generate text, analyze sentiment, translate languages, and much more.

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70+ Best and Unique Python Machine Learning Projects with source code [2023]

Mlearning.ai

We have the IPL data from 2008 to 2017. Most dominant colors in an image using KMeans clustering In this blog, we will find the most dominant colors in an image using the K-Means clustering algorithm, this is a very interesting project and personally one of my favorites because of its simplicity and power.