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    Posts about Data Science:

    Understanding Neural Networks and the Training Process

    Training a neural network involves a lot of mathematics, including linear algebra and multivariate calculus, and a lot of computation. The purpose of...
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    Two classifiers being combined into a single classifier. In general, the decision boundaries of the two classifiers cannot merely be superimposed; instead new boundaries must be learned that respect both tasks.

    Sequential Learning through Knowledge Distillation and Elastic Weight Consolidation

    In the last blog post, we saw that neural networks can be simplified (or pruned) to alleviate their complexity and cost for computation. Often small...
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    Pruning ResNets for Fun and Profit

    What are Neural Networks? Neural networks are highly parameterized functions which can be trained to fit/represent/model data. Parameterized models...
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