Data AnnotationFive reasons why data annotation matters
Data annotation is the invisible infrastructure behind our AI-powered future. Learn more about this industry and why it’s never mattered more.
Data AnnotationFive approaches to data labeling for machine learning projects
In this article we cover five common approaches to data labeling for machine learning, along with pros and cons for each.
Data AnnotationWhat is text annotation? Five different types of annotations
To train NLP algorithms, large annotated text datasets are required. Learn more with a brief introduction to five common types of text annotation.
Data AnnotationWhat is audio classification?
Looking for an introduction to audio classification? In this article we discuss different types of audio classification and their use in machine learning projects.
Data AnnotationHow self-agreement can improve your training data
Are you evaluating your annotation team for quality? Read why self-agreement checks are critical for a proper evaluation.
Data AnnotationeCommerceWhat is product categorization?
Learn about product categorization (also known as product classification) and how it’s crucial to the eCommerce industry.
Data AnnotationFive types of image annotation and their use cases
Wondering which image annotation types best suit your project? In this article, we introduce five types of image annotation and their applications.
Data AnnotationHow to get annotated data for machine learning
Capturing enough accurate, quality data at scale is a common challenge. Discover four ways to source raw data for machine learning, and how to go about annotation process.
Data AnnotationUnderstanding text analysis tools
Text analysis tools offer a multitude of benefits, but how do they work? We look at types of AI text analysis, their use cases and how to get started.
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