Neural Networks Demystified [Part 1: Data and Architecture]

推荐理由

One of the clearest walkthroughs I've seen online is a short series of very short videos by Stephen C Welch [2] [3].

强烈推荐film42 · 原文2015年2月

说明

这是2014年由Welch Labs发布的一部教程，主题归在Machine learning & deep learning。它讲的是neural networks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 of a short series by Welch Labs on building a complete neural network in Python. It introduces the data and the architecture of a simple network before later parts cover forward propagation, gradient descent, and backpropagation.这些读者给出的理由，核心是：HN commenters point beginners to this series as one of the clearest short walkthroughs of how neural networks and backpropagation work.讲法不绑某一条新闻，过几年仍然可以当材料看。从2015年到2018年，有3位不同的读者在3个不同月份把它推荐出来，其中明确叫别人去看的有1次。适合打开电脑跟着做的人。如果只听不练，这集的价值会少一半。如果已经会了基本定义，就把注意力放在它怎么把neural networks变成能跟着复述的例子。

视频信息

频道

Welch Labs

时长

3 分 7 秒

发布年份

2014

同主题更多

• The spelled-out intro to neural networks and backpropagation: building micrograd
• But what is a neural network? | Deep learning chapter 1
• AlphaGo - The Movie | Full award-winning documentary
• Transformers, the tech behind LLMs | Deep Learning Chapter 5
• USENIX Security '18-Q: Why Do Keynote Speakers Keep Suggesting That Improving Security Is Possible?
• Lecture 1 | Machine Learning (Stanford)