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Category: Machine Learning

We can use data to train machines to perform tasks instead of explicitly programming them. This category will cover experiments utilizing neural networks, graph neural networks, and probabilistic approaches to train machines to perform tasks using data


Recent successes in machine learning owe their power to transfer and representation learning. Transfer learning allows us to fine-tune a model trained on one task to a new task using fewer training examples and improving accuracy. Representation learning is allowing a system to discover the representations required for feature detection…

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