AWS Machine Learning Blog

NOVEMBER 1, 2024

Fine-tuning is a powerful approach in natural language processing (NLP) and generative AI , allowing businesses to tailor pre-trained large language models (LLMs) for specific tasks. This process involves updating the model’s weights to improve its performance on targeted applications.

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Data Preparation Machine Learning Machine Learning ML 95

AWS Machine Learning Blog

NOVEMBER 27, 2023

While this data holds valuable insights, its unstructured nature makes it difficult for AI algorithms to interpret and learn from it. According to a 2019 survey by Deloitte , only 18% of businesses reported being able to take advantage of unstructured data. Clean data is important for good model performance.

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Data Preparation AI AI Python 96

AWS Machine Learning Blog

SEPTEMBER 14, 2023

“Data locked away in text, audio, social media, and other unstructured sources can be a competitive advantage for firms that figure out how to use it“ Only 18% of organizations in a 2019 survey by Deloitte reported being able to take advantage of unstructured data. The majority of data, between 80% and 90%, is unstructured data.

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AWS Machine Learning Machine Learning Data Scientist 120

Kaggle

JULY 29, 2020

[link] David Mezzetti is the founder of NeuML, a data analytics and machine learning company that develops innovative products backed by machine learning. He previously co-founded and built Data Works into a 50+ person well-respected software services company. Do you have any advice for those just getting started in data science?

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ETL Data Scientist Data Science Machine Learning 71

AWS Machine Learning Blog

MARCH 28, 2024

Data preparation In this post, we use several years of Amazon’s Letters to Shareholders as a text corpus to perform QnA on. For more detailed steps to prepare the data, refer to the GitHub repo. For step-by-step instructions, refer to the GitHub repo. SageMaker JumpStart is at the center of this solution.

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AWS Machine Learning Machine Learning AI 134

The MLOps Blog

APRIL 5, 2023

For example, Modularizing a natural language processing (NLP) model for sentiment analysis can include separating the word embedding layer and the RNN layer into separate modules, which can be packaged and reused in other NLP models to manage code and reduce duplication and computational resources required to run the model.

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ML ML Machine Learning Machine Learning 69

AWS Machine Learning Blog

SEPTEMBER 11, 2024

The Inferentia chip became generally available (GA) in December 2019, followed by Trainium GA in October 2022, and Inferentia2 GA in April 2023. The benchmark used is the RoBERTa-Base, a popular model used in natural language processing (NLP) applications, that uses the transformer architecture.

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AWS ML ML Clustering 100