AWS Machine Learning Blog

MAY 31, 2024

In this blog post and open source project , we show you how you can pre-train a genomics language model, HyenaDNA , using your genomic data in the AWS Cloud. Amazon SageMaker Amazon SageMaker is a fully managed ML service offered by AWS, designed to reduce the time and cost associated with training and tuning ML models at scale.

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AWS ML ML Machine Learning 120

AWS Machine Learning Blog

SEPTEMBER 29, 2023

In late 2023, Planet announced a partnership with AWS to make its geospatial data available through Amazon SageMaker. This example uses the Python client to identify and download imagery needed for the analysis. Model training After the data has been downloaded with the Planet Python client, the segmentation model can be trained.

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Machine Learning Machine Learning ML ML 137

Mlearning.ai

MARCH 15, 2023

Build a Stocks Price Prediction App powered by Snowflake, AWS, Python and Streamlit — Part 2 of 3 A comprehensive guide to develop machine learning applications from start to finish. I have checked the AWS S3 bucket and Snowflake tables for a couple of days and the Data pipeline is working as expected. Until next time… Happy coding !!

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Python AWS Exploratory Data Analysis Machine Learning 52

Heartbeat

MAY 29, 2023

Use a representative and diverse validation dataset to ensure that the model is not overfitting to the training data. Source: AWS re:Invent Storage: LLMs require a significant amount of storage space to store the model and the training data. This can include user manuals, FAQs, and chatbots for real-time assistance.

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Machine Learning Machine Learning Natural Language Processing Data Preparation 78

AWS Machine Learning Blog

JULY 20, 2023

This final estimator’s training process often uses cross-validation. All these solutions include a meta-estimator (for example in an AWS Lambda function) that invokes each model and implements the blending or voting function. We also implement a k-fold cross validation function.

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ML ML Cross Validation AWS 98