AWS Machine Learning Blog

JANUARY 5, 2024

The suite of services can be used to support the complete model lifecycle including monitoring and retraining ML models. Query training results: This step calls the Lambda function to fetch the metrics of the completed training job from the earlier model training step.

Data Science 133

Data Science Data Drift DevOps Auto-complete 133

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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Data Drift Auto-complete ML Automation 121

The MLOps Blog

JUNE 27, 2023

Learn more The Best Tools, Libraries, Frameworks and Methodologies that ML Teams Actually Use – Things We Learned from 41 ML Startups [ROUNDUP] Key use cases and/or user journeys Identify the main business problems and the data scientist’s needs that you want to solve with ML, and choose a tool that can handle them effectively.

Machine Learning 134

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ODSC - Open Data Science

OCTOBER 11, 2023

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. Data issues like label errors, outliers, duplicates, data drift, and low-quality examples significantly hamper model performance.

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Auto-classification Auto-complete Data Drift Machine Learning 52

The MLOps Blog

MARCH 12, 2024

Monitoring Monitor model performance for data drift and model degradation, often using automated monitoring tools. Optimization: Use database optimizations like approximate nearest neighbor ( ANN ) search algorithms to balance speed and accuracy in retrieval tasks.

Prompt Engineer 52

Prompt Engineer Prompt Engineering Large Language Models LLM 52

Topbots

JUNE 29, 2023

This vision is embraced by conversational interfaces which allow humans to interact with data using language, our most intuitive and universal channel of communication. After parsing a question, an algorithm encodes it into a structured logical form in the query language of choice, such as SQL. in the data.

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Algorithm Auto-complete Data Scientist Auto-classification 52