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utkuufuk.com | ||
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teddykoker.com
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| | | | | A few posts back I wrote about a common parameter optimization method known as Gradient Ascent. In this post we will see how a similar method can be used to create a model that can classify data. This time, instead of using gradient ascent to maximize a reward function, we will use gradient descent to minimize a cost function. Lets start by importing all the libraries we need: | |
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blog.c0nrad.io
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| | | | | [AI summary] The author describes building a neural network to classify Star Wars Unlimited cards into heroism, villainy, or neutrality using a Coursera course's knowledge, focusing on binary classification and future plans for more complex tasks. | |
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blog.ouseful.info
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| | | | | Reading a post just now on Logo detection using Apache MXNet, a handy tutorial on how to train an image classifier to detect brand logos using Apache MXNet, a deeplearning package for Python, I noted a reference to the MXNet Model Zoo. The Model Zoo is an ongoing project to collect complete models [from the... | |
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dev-discuss.pytorch.org
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| | | TL;DR: Previously, torchdynamo interrupted compute-communication overlap in DDP to a sufficient degree that DDP training with dynamo was up to 25% slower than DDP training with eager. We modified dynamo to add additional... | ||
