#349 overall
Machine Learning
University of Oxford
2 recommenders · 2 threads · recommended in 2 years, 2015–2016 · score 1.5
A university machine learning course from Oxford, taught by Nando de Freitas and published around 2015, covering core ML methods and models. Commenters describe it as a free, high-quality MOOC-style course.
Commenters recommend it as a free, high-quality alternative to short introductory courses, with one calling it perhaps the most recent ML MOOC available.
Machine Learning & AIintermediatefreevideo lectures#machine learning#neural networks#probabilistic models#de freitas#statistics
Recommendations by year
20062026
If you want more than a 4 lecture course, I recommend Nando de Freitas's course. It's very high quality and free.
https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearni...
This is fantastic! I've been meaning to make an RNN to generate EDM.
For begineers, I'd like to summarize some excellent resources to start:
- Coursera course by Andrew Ng (he explains everything magically. The best course I've done online) https://class.coursera.org/ml-003/lecture
- Neural Networks and Deep Learning neuralnetworksanddeeplearning.com/ (I highly recommend trying to write your own backprop and MNIST dataset classifier. I wrote in JS and gave me a lot of confidence)
- Oxford ML class (2015) https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearni... (perhaps the the most recent MOOC on ML online. Things are progressing so fast in deep learning that it's worthwhile to do multiple ML courses to get different perspectives)
- I also enjoyed http://karpathy.github.io/2015/05/21/rnn-effectiveness/ for inspiration and the video https://www.youtube.com/watch?v=xKt21ucdBY0 is a FANTASTIC summary. HN earlier pointed our the course videos are out http://cs224d.stanford.edu/syllabus.html
- Again for inspiration into big challenges, this talk from Andrew Ng is a good one https://www.youtube.com/watch?v=W15K9PegQt0