OPEN DATASETS: This list of open datasets is great for aspiring data scientists.
INTRO TO DEEP LEARNING: This video series on youtube, from DeepLearning.TV, is a great place to learn about the basics of deep learning. It also is a great resource for more experienced practitioners because it is pretty comprehensive.
INTERACTIVE OPTIMIZATION TUTORIAL: This is an interactive optimization tutorial that is great for anyone looking to learn more about machine learning or deep learning.
STANFORD MACHINE LEARNING: For those interested in an advanced version of Andrew Ng’s machine learning class on Coursera, you can go to youtube for the real Stanford course.
OXFORD COURSE ON DEEP LEARNING: This class, taught by Nando de Frietas of Google Deepmind and Oxford University, is likely my favorite course on machine learning. It’s great for those with strong math skills and a little machine learning knowledge.
DEEP LEARNING FOR COMPUTER VISION: This Stanford class, CS231n, is taught by Andrej Karpathy, a recent Stanford PhD graduate who now works at OpenAI. It covers deep learning from an imaging perspective and is excellent for anyone interested in deep learning. It is the prerequisite for Stanford’s CS224d listed below.
DEEP LEARNING FOR NLP: This Stanford class, CS224d, is taught by Richard Socher, a NLP whiz who is now chief scientist at Salesforce. The class covers word vectors, language models, recurrent neural nets and recursive neural nets. It also briefly covers TensorFlow.