Lesson 17: Deep Learning Foundations to Stable Diffusion

(All lesson resources are available at http://course.fast.ai.) In this lesson, we discuss the importance of weight initialization in neural networks and explore various techniques to improve training. We start by introducing changes to the miniai library and demonstrate the use of HooksCallback and ActivationStats for better visualization. We then dive into the importance of having zero mean and unit standard deviation in neural networks and introduce the Glorot (Xavier) initialization.

We also cover variance, standard deviation, and covariance, and their …

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