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Breaking standard machine learning paradigms: few-shot learning for computer vision
About This Webinar
A talk by Isha Chaturvedi.
This talk will explore the concept of few-shot learning and its applications in computer vision.
Few-shot learning is a machine learning paradigm that allows a model to learn and generalize from a small number of examples. The talk will cover how this approach differs from traditional machine learning methods, which typically require large amounts of data.
Isha will discuss various techniques for implementing few-shot learning in computer vision, such as meta-learning, and demonstrate how these techniques can improve the performance of models on tasks such as image classification and object detection.
Who can view: Everyone
Webinar Price: Free
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Since our inception, we’ve achieved a great deal. But we don’t rest on our laurels. We’re constantly looking for ways in which we can evolve and further engage, educate, and inspire our community. Got an idea? Great. We’d love to hear from you.
Our mission
Our mission is to help develop the next generation of machine intelligence specifically focusing on accelerating AI at the edge. For new and groundbreaking start-ups, we want to inspire and inform your journey, and for those giants in the space, we want to provide the tools you need to innovate and continue to propel your growth.
What we do
Since our inception, we’ve achieved a great deal. But we don’t rest on our laurels. We’re constantly looking for ways in which we can evolve and further engage, educate, and inspire our community. Got an idea? Great. We’d love to hear from you.
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