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Explore what is involved in the collection and labeling of training data that is used to build computer vision models.
Choosing a data annotation partner is one of the most crucial decisions machine learning teams can make because it directly affects their go-to-market strategy. Crucial decisions call for careful planning. Explore our checklist to help you find the right AI data solutions partner.
Video annotation enriches video data by adding object information tags across every frame. Discover different video annotations, their popular computer vision applications and the benefits of video labeling automation.
Discover a robust guide to image segmentation, a data labeling technique used to segment object pixels to train computer vision models
Learn more about the myths surrounding data labeling workflows and budgets in order to build effective labeling strategies for machine learning.
As the list of managed data service providers grows, how do you decide which to trust? Find tips for selecting the right data annotation company for your project.
Reinforcement learning is a dynamic AI tool that can help improve business decision-making processes. Learn more about its unique value proposition in this primer.
A recommender system uses machine learning to predict the likelihood that a user will prefer a particular item or service. Learn how these systems facilitate great experiences that keep customers coming back for more.
The best way to avoid haphazard automation efforts is to put a detailed roadmap in place. Discover expert tips for developing a plan and putting it in action.
More and more brands are using machine learning and computer vision in their advertising. Discover the risks and benefits.
If you train your model with biased data, it will learn and even amplify those biases. Here’s how to address bias in artificial intelligence models.
Uncover the history of computer vision, deep learning and neural networks, and learn how their developments could meaningfully impact businesses and society as a whole.
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