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An introduction to machine learning training data

Published by Appen

This whitepaper emphasizes the critical role of high-quality and large-scale training data in the success of machine learning models. It outlines the importance of both data quantity and quality, explaining how diverse and well-annotated data helps AI systems recognize patterns and make accurate predictions. The paper also explores different data sources, including real-world usage, surveys, public datasets, and engineered data, and highlights the challenges of ensuring data accuracy and relevance. Finally, it emphasizes the need for expert vendors to manage and curate training data effectively.

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Related Categories Artificial Intelligence, Deep Learning, AI Platforms, AI Development Tools, Unsupervised Learning, Reinforcement Learning, ML Algorithms, Data Preprocessing, Model Training, Adaptive Learning, Learning Analytics, Virtual Classrooms, Education Management

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