Stanford's CS229 was also on Coursera.<p><a href="https://class.coursera.org/ml/lecture/preview" rel="nofollow">https://class.coursera.org/ml/lecture/preview</a>
I wrote a blog post with some material suggestions to learn Machine Learning. If you want, visit my blog post:<p><a href="http://pauloortins.com/resources-to-become-a-ninja-machine-learning/" rel="nofollow">http://pauloortins.com/resources-to-become-a-ninja-machine-l...</a>
As a reference, you'll want one or two of the Big 6 texts, by Murphy, Koller/Friedman, Bishop, MacKay, and Hastie et al ESL. The first review is good <a href="http://www.amazon.com/product-reviews/0262018020/ref=dp_top_cm_cr_acr_txt?showViewpoints=1" rel="nofollow">http://www.amazon.com/product-reviews/0262018020/ref=dp_top_...</a><p>Also, there are many freely available texts on ML, data mining, stats/prob distributions, linear algebra, optimization etc, incl Barber, Mackay and ESL. See <a href="http://www.reddit.com/r/MachineLearning/comments/1jeawf/machine_learning_books/" rel="nofollow">http://www.reddit.com/r/MachineLearning/comments/1jeawf/mach...</a>
For a second, I misread this as "Machine Learns Course Materials". Must make this happen - wonder if I can use these machine learning course materials to help.