CS231n-2017-Summary and deep-learning-notes
About CS231n-2017-Summary
mbadry1/CS231n-2017-Summary
After watching all the videos of the famous Standford's CS231n course that took place in 2017, i decided to take summary of the whole course to help me to remember and to anyone who would like to know about it. I've skipped some contents in some lectures as it wasn't important to me.
This document summarizes the key concepts from Stanford's CS231n 2017 course on Convolutional Neural Networks for Visual Recognition. It provides an overview of image classification, neural networks, loss functions, and optimization techniques. This resource is ideal for anyone looking for a condensed explanation of deep learning fundamentals applied to computer vision tasks, particularly those who have viewed the lectures and want a review.
About deep-learning-notes
albertpumarola/deep-learning-notes
My CS231n lecture notes
This collection of study notes helps you understand core concepts and advanced topics in deep learning. It condenses lectures from a top university course and key texts into a single, organized PDF or individual chapter PDFs. Anyone studying or working with artificial intelligence and machine learning will find this useful for learning or quick reference.
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