AWS Machine Learning Blog

JANUARY 5, 2024

This post was written in collaboration with Bhajandeep Singh and Ajay Vishwakarma from Wipro’s AWS AI/ML Practice. Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models.

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Mlearning.ai

JUNE 23, 2023

Auto Data Drift and Anomaly Detection Photo by Pixabay This article is written by Alparslan Mesri and Eren Kızılırmak. After deployment, Machine Learning model needs to be monitored. Model performance may change over time due to data drift and anomalies in upcoming data.

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ODSC - Open Data Science

OCTOBER 11, 2023

Be sure to check out his talk, “ How to Practice Data-Centric AI and Have AI Improve its Own Dataset ,” there! Machine learning models are only as good as the data they are trained on. Even with the most advanced neural network architectures, if the training data is flawed, the model will suffer.

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AWS Machine Learning Blog

NOVEMBER 9, 2023

Building out a machine learning operations (MLOps) platform in the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML) for organizations is essential for seamlessly bridging the gap between data science experimentation and deployment while meeting the requirements around model performance, security, and compliance.

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AWS Machine Learning Blog

MARCH 1, 2023

Statistical methods and machine learning (ML) methods are actively developed and adopted to maximize the LTV. Challenges In this section, we discuss challenges around various data sources, data drift caused by internal or external events, and solution reusability. The interval of logs is not uniform.

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The MLOps Blog

JUNE 27, 2023

How to evaluate MLOps tools and platforms Like every software solution, evaluating MLOps (Machine Learning Operations) tools and platforms can be a complex task as it requires consideration of varying factors. For example, if you use AWS, you may prefer Amazon SageMaker as an MLOps platform that integrates with other AWS services.

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AWS Machine Learning Blog

SEPTEMBER 21, 2023

In this post, we discuss how United Airlines, in collaboration with the Amazon Machine Learning Solutions Lab , build an active learning framework on AWS to automate the processing of passenger documents. “In The process relies on manual annotations to train ML models, which are very costly.

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