+46

Deep Learning and AI. Convalutional Neural Networks for Visual Recognition.

This course has helped me immensely with my understanding of Deep Learning, Computer Vision and AI. This is a great place to start if you have interest in any of these fields 😊 They use python, but you don't need to use it to get the concepts. I am currently pursuing a master's degree in cybernetics and robotics. http://cs231n.stanford.edu Fall 2016: https://www.youtube.com/playlist?list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC Spring 2017: http://www.youtube.com/playlist?list=PLC1qU-LWwrF64f4QKQT-

12/16/2017 4:50:21 PM

Bjarte Mehus Sunde

19 Answers

New Answer

+14

@Devansh https://www.quora.com/What-is-the-difference-between-Deep-Learning-Machine-learning-and-Artificial-Intelligence-Is-Deep-learning-related-to-data-science

+8

Thanks for posting this! ☺

+7

I always wanted to pursue a degree in cybernetics but I can't. Well, you are in fabulous stream and thanks for the post.

+5

tensorflow is helpful for machine learning and deep learning AI as well..it's a open source library developed by Google..works with python

+5

also udacity academy very helpful..for ai ..related videos

+4

Hi and thanks for sharing the above links! What sorts of specific applications of computer vision you’re looking at, currently? :) I’m quite interested in the applicability of CV in the monitoring and navigation of harsh environments, and might consider that as a topic for further study (sometime in the near future, hopefully). In my current role, the only area which is AI-related is the condition based monitoring of machinery (although CBM is still in its early stages where I work, and is therefore not the main focus of my job, sadly). I am interested in languages/natural language processing as well, and so deep learning in machine translation is also an area of particular interest. So for now, I’m working towards having a good understanding of the principles behind AI, and its potential capabilities :)

+4

thanks for the post..

+4

thanks

+3

thanks!

+3

Can this be useful for Data Science?

+3

thanks!

+3

@Wes I'm not sure what you mean with kernel. The most important things I've learned form this course; understanding how backpropagation works, and seeing how Convolutional Neutral Networks should be built, trained and tuned.

+3

*Bookmarked

+2

Thank you.

+2

Looking forward to checking this out, thanks for the links.

+2

https://code.sololearn.com/W95XqzQyJv4s/?ref=app 👍

+1

What was the most impotant kernel that you gathered from this course?

+1

Thank you Bjarte Mehus Sunde.