Unite.AI

JUNE 24, 2024

This is the reason why data scientists need to be actively involved in this stage as they need to try out different algorithms and parameter combinations. This is not ideal because data distribution is prone to change in the real world which results in degradation in the model’s predictive power, this is what you call data drift.

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AWS Machine Learning Blog

MARCH 1, 2023

Challenges In this section, we discuss challenges around various data sources, data drift caused by internal or external events, and solution reusability. For example, Amazon Forecast supports related time series data like weather, prices, economic indicators, or promotions to reflect internal and external related events.

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The MLOps Blog

JUNE 27, 2023

Amazon SageMaker Ground Truth SageMaker Ground Truth is a fully managed data labeling service designed to help you efficiently label and annotate your training data with high-quality annotations. The platform provides a comprehensive set of annotation tools, including object detection, segmentation, and classification.

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The MLOps Blog

MARCH 12, 2024

Monitoring Monitor model performance for data drift and model degradation, often using automated monitoring tools. It involves transforming textual data into numerical form, known as embeddings, representing the semantic meaning of words, sentences, or documents in a high-dimensional vector space.

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