Contrastive Learning: A Tutorial | Built In
Contrastive Learning: A Tutorial | Built In
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Artificial Intelligence | AI on Instagram: "SimCLR (Simple Contrastive Learning of Representations) is a technique for self-supervised learning, primarily designed to learn representations from unlabeled data. The main idea behind SimCLR is to use contrastive learning to map similar data points closer together in the representation space while pushing dissimilar ones apart. This is achieved by creating augmented views of the same image and training a neural network to recognize that these augmen
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Artificial Intelligence | AI on Instagram: "Contrastive learning is a type of self-supervised learning where the goal is to learn representations by comparing pairs of data. Instead of predicting missing parts of data like other self-supervised algorithms, it teaches a model to bring similar examples (called positive pairs) closer in the embedding space while spacing different ones (called negative pairs) farther apart. For instance, two different versions of the same image (rotated and cropped)
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