Lecture 1 | Introduction to Convolutional Neural Networks for Visual Recognition

推荐理由

The Stanford course is pretty good.

推荐dahart · 原文2018年4月

说明

这是2017年由Stanford University School of Engineering发布的一部课堂讲座，主题归在Machine learning & deep learning。它讲的是computer vision deep learning这一支里的具体问题，而不是把整个领域扫一遍。适合第一次接触、还没有先修课的人。内容上可以概括成：The first lecture of Stanford's CS231n course on convolutional neural networks for visual recognition. It surveys the history and key challenges of computer vision, from the Cambrian explosion and Hubel and Wiesel to ImageNet.这些读者给出的理由，核心是：HN recommends the CS231n lectures as a solid, applied deep learning course for self-study.它贴着当时的技术，看的时候要记得那是那个年份的判断。从2018年到2025年，有2位不同的读者在2个不同月份把它推荐出来，其中明确叫别人去看的有0次。节奏接近上课，可以暂停做笔记。它假设你愿意跟着一条推导走完。如果已经会了基本定义，就把注意力放在它怎么把computer vision deep learning变成能跟着复述的例子。

视频信息

频道

Stanford University School of Engineering

时长

57 分 57 秒

发布年份

2017

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