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Unsupervised Feature Learning and Deep Learning Tutorial
- ppymou 11y agoFor anyone interested, I have been really interested in deep learning and have been using the following resources: For image processing (CNN) https://cs231n.github.io/ https://cs231n.github.io/ For natural language processing (RNN) http://cs224d.stanford.edu/syllabus.html http://cs224d.stanford.edu/syllabus.html I also found the following coursera helpful https://www.coursera.org/course/neuralnets https://www.coursera.org/course/neuralnets https://www.coursera.org/learn/machine-learning https://www.coursera.org/learn/machine-learning
- wodenokoto 11y agoDoes anyone know how to access past courses on coursera if you didn't sign up in a timely manner?
- lopuhin 11y agoI think you just sign in and click on a big green button "Go to Course" on the right - at least it worked for me with neuralnets course by Hinton, which is really great.
- aethertap 11y agoIt depends on the course, some courses are kept available and others are shut down after the action is over. I think the choice is left up to the instructors. I started downloading all of the videos when I sign up for a course for this reason actually, because I tend to go through them too slowly to finish with the main group.
- JPKab 11y agoThanks. I really appreciate it when folks like you on HN post learning materials in the comments.
- Omnipresent 11y agoThese are great resources. There is also a ML class offered by Georgia Tech at Udacity under the OMSCS program. https://www.udacity.com/wiki/ml/GT https://www.udacity.com/wiki/ml/GT
- aswanson 11y agoThank you, a lot of the papers in DL/Sparse Coding aren't as clear as the sources you shared.
- theviajerock 11y agoThanks, i will see it, seems very interesting.
- rogeryu 11y ago> If you are not familiar with these ideas, we suggest you go to this Machine Learning course and complete sections II, III, IV (up to Logistic Regression) first. What is the link to that course?
- SandB0x 11y agoI assume it is http://cs229.stanford.edu/ http://cs229.stanford.edu/
- rogeryu 11y agoThat is normal class, not online if I'm correct.
- thomasrossi 11y agoThe group is held by Prof. Ng which has a ML course on coursera https://www.coursera.org/learn/machine-learning https://www.coursera.org/learn/machine-learning - lecture notes of the in class course are here http://cs229.stanford.edu/materials.html http://cs229.stanford.edu/materials.html (but without the lecture it may be.. without the lecture:))
- DoggettCK 11y agoDefinitely worth it. I had to drop out around week 5 due to a lack of time, but just started a new job that'll take me back to 40-hour weeks (down from 80-100), so I'll give it another shot next time they run the course.
- haraball 11y agoThe latest session started today, from 5 Oct to 27 Dec.
- aswanson 11y agoNg is one of those great profs that combine the rare gifts of being able to teach as well as be a leader in the field at the same time. I've had profs that are far less accomplished and far more arrogant. There's probably a correlation between those features, now that I think about it.
- Omnipresent 11y agoIs there a similar tutorial or resource that shows how to do face detection (not recognition) using deep learning. I came across tutorial from kaggle [1] but I'm looking for something that uses ML to detect where the faces are in an image. [1] - http://danielnouri.org/notes/2014/12/17/using-convolutional-neural-nets-to-detect-facial-keypoints-tutorial/ http://danielnouri.org/notes/2014/12/17/using-convolutional-...