AWS Machine Learning Blog

MAY 1, 2025

Best practices for data preparation The quality and structure of your training data fundamentally determine the success of fine-tuning. Our experiments revealed several critical insights for preparing effective multimodal datasets: Data structure You should use a single image per example rather than multiple images.

AWS 85

AWS ML ML AI 85

AWS Machine Learning Blog

AUGUST 22, 2023

Both the training and validation data are uploaded to an Amazon Simple Storage Service (Amazon S3) bucket for model training in the client account, and the testing dataset is used in the server account for testing purposes only. Details of the data preparation code are in the following notebook.

Machine Learning 98

Machine Learning Machine Learning AWS ML 98

Flipboard

AUGUST 17, 2023

Option C: Use SageMaker Data Wrangler SageMaker Data Wrangler allows you to import data from various data sources including Amazon Redshift for a low-code/no-code way to prepare, transform, and featurize your data. She has extensive experience in machine learning with a PhD degree in Computer Science.

ML 123

ML ML AWS Data Warehouse 123

AWS Machine Learning Blog

SEPTEMBER 11, 2024

Around this time, industry observers reported NVIDIA’s strategy pivoting from its traditional gaming and graphics focus to moving into scientific computing and data analytics. in 2012 is now widely referred to as ML’s “Cambrian Explosion.” The union of advances in hardware and ML has led us to the current day.

AWS 117

AWS ML ML Clustering 117

Tableau

FEBRUARY 24, 2021

However, another motivation was a personal reflection on a field that did not yet exist a little over a decade ago when I first began my advanced studies in computer science. As data science work grew in complexity, data scientists became less generalized and more specialized, often engaged in specific aspects of data science work.

Data Science 111

Data Science Data Scientist Data Visualization Computer Science 111

Tableau

FEBRUARY 24, 2021

However, another motivation was a personal reflection on a field that did not yet exist a little over a decade ago when I first began my advanced studies in computer science. As data science work grew in complexity, data scientists became less generalized and more specialized, often engaged in specific aspects of data science work.

Data Science 52

Data Science Data Scientist Data Visualization Computer Science 52