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Mike Jordan at Berkeley recommends the following books. The list is definitely on the more rigorous side (aimed at more researchers than practitioners), but going through these books (along with the requisite programming experience) is a useful, if not painful, exercise. This list of intermediate-level books was published a few years ago, but is still interesting.
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I don't believe I'm up to speed on machine learning and thought I'd check out the list, but at the top of the list is a statistical text I used in college and I'm familiar with one or two others which are also statistical texts. Are you sure this is the right list? I would have imagined that the machine learning list would have been focused on neural networks and such.
It's Mike Jordan's list and a bit outdated. Mike is a famous professor at Berkeley University. There's a come back of AI now, known as deep learning by ML practitioners.
For those not familiar with these abbreviations, ML is machine learning and AI is artificial intelligence.