CS231n-2017-Summary and cs230-2018-autumn
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 cs230-2018-autumn
maxim5/cs230-2018-autumn
All lecture notes, slides and assignments for CS230 course by Stanford University.
This is a collection of all lecture notes, slides, and assignments from Stanford University's CS230 Deep Learning course, taught in Autumn 2018. It provides a structured curriculum for anyone looking to learn about deep learning, with materials to study and practice problems to complete. It is ideal for students, self-learners, or educators who want to follow a university-level deep learning course.
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