Stanford is offering a MOOC on Statistical Learning. It's free, more details here. The course has already started a couple of days back, but you can still watch the archives once registered to the course. The Coursera ML course is really good, but sometimes it deep dives into Maths, which makes it not for everyone. The good thing about the Stanford offering is
This is not a math-heavy class, so we try and describe the methods without heavy reliance on formulas and complex mathematics.
On the other side, the focus is on R for statistical analysis. For those who are into Python, they can still go through the course. DataRobot is planning for a follow on blogs for the techniques discussed during the Stanford sessions using Python. DataRobot is still in the stealth mode, so you can follow their blog here using Feedly or some other RSS aggregator.
Note that the corresponding book `An Introduction to Statistical Learning with Applications in R` for the course can be downloaded here for free.
This is not a math-heavy class, so we try and describe the methods without heavy reliance on formulas and complex mathematics.
On the other side, the focus is on R for statistical analysis. For those who are into Python, they can still go through the course. DataRobot is planning for a follow on blogs for the techniques discussed during the Stanford sessions using Python. DataRobot is still in the stealth mode, so you can follow their blog here using Feedly or some other RSS aggregator.
Note that the corresponding book `An Introduction to Statistical Learning with Applications in R` for the course can be downloaded here for free.
This is not a math-heavy class, so we try and describe the methods without heavy reliance on formulas and complex mathematics. feng shui master
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