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blog.alexalemi.com
| | jxmo.io
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| | A primer on variational autoencoders (VAEs) culminating in a PyTorch implementation of a VAE with discrete latents.
| | colah.github.io
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| | blog.evjang.com
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| | This is a tutorial on common practices in training generative models that optimize likelihood directly, such as autoregressive models and ...
| | programminghistorian.org
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| [AI summary] The text provides an in-depth explanation of using neural networks for image classification, focusing on the Teachable Machine and ml5.js tools. It walks through creating a model, testing it with an image, and displaying results on a canvas. The text also discusses the limitations of the model, the importance of training data, and suggests further resources for learning machine learning.