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blog.glcs.io | ||
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kavita-ganesan.com
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| | | | | This article examines the parts that make up neural networks and deep neural networks, as well as the fundamental different types of models (e.g. regression), their constituent parts (and how they contribute to model accuracy), and which tasks they are designed to learn. | |
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dennybritz.com
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| | | | | All the code is also available as an Jupyter notebook on Github. | |
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pyimagesearch.com
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| | | | | In this tutorial, you will learn what gradient descent is, how gradient descent enables us to train neural networks, variations of gradient descent, including Stochastic Gradient Descent (SGD), and how SGD can be improved using momentum and Nesterov acceleration. | |
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yann.lecun.com
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| | | LeNet Demo | ||
