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CS231n Winter 2016: Lecture1: Introduction and Historical Context

Andrej Karpathy

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Beginner. No background in the topic needed.

462K views10 years ago2 recommendations

AI and machine learningComputer scienceNeural networks and deep learningComputer visionTraining and serving models

Andrej Karpathy introduces Stanford's CS231n course on convolutional neural networks and provides a historical overview of computer vision.

Stanford Winter Quarter 2016 class: CS231n: Convolutional Neural Networks for Visual Recognition. Lecture 1. Get in touch on Twitter @cs231n, or on Reddit /r/cs231n.

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2 people recommend this

What people say. Highly recommended as an excellent starting point for learning computer vision and deep learning.

neel8986on Hacker News • Recommends

On “Ask HN: How to Seriously Start with Machine Learning and AI”

…e books and courses You can get more in-depth knowledge of Machine learning from following sources 1)Nando machine learning course ( link ) 2)Bishops book ( link ) Especially Bishops book is really deep and covers almost all basic concepts. Now for recent advances in Deep learning. I will suggest two brilliant courses from Stanford 1) Vision ( link to this video ) 2) NLP ( link ) The Vision course by Karparthy can be a very good introduction to Deep learning. Also, the mother book for deep learning ( link )is good…

igraviouson Hacker News • Recommends

On “Ask HN: Best introductory video courses on ML and Deep Learning?”

fast.ai Making neural nets uncool again. fast.ai is dedicated to making the power of deep learning accessible to all.0 Udacity. Intro to Machine Learning: Pattern Recognition for Fun and Profit1 MIT 6.S099: Artificial General Intelligence2 Lecture Series on Artificial Intelligence by Prof. P. Dasgupta, Department of Computer Science & Engineering, Indian Institute of Technology, Kharagpur3 DeepMind. Reinforcement Learning Course by David Silver4 Stanford Winter Quarter 2016 class: CS231n: Convolutional Neural Networks for Visual Recognition.5 0 link 1 link 2 link 3 link 4 link 5 link to this video

kaffeinecomaon Hacker News • Mentions

On “Neural Networks Are Impressively Good at Compression”

No need to apologize- I learned SO much from your blog, thank you. I didn't realize the course was online ( link to this video ). Also, looks like there's a subreddit for it as well: link It's really wonderful that all of this is freely available, thank you.

tgittoson Hacker News • Mentions

On “Ask HN: Daily practices for building AI/ML skills?”

…that I spend skilling up in AI. I've been following the space for about 15 years and have done a bunch of self learning of earlier ML techniques (the early Stanford ML MooCs) so I'm not coming in cold. What I'm doing is: - Following along with Karpathy's videos, which has been mentioned: link - About to follow along with CS 231n, also mentioned: link to this video - Trying ideas and theories in a Jupyter notebook - Reading papers I would agree with other commenters that recommend learning how to implement a paper. As someone who barely managed to get their undergraduate degree, papers are intimidating. I don't know half the terms and the equations, while short, look complex. Often it will take me sev…