A Wealth of Machine Learning Links
January 21, 2014
Anyone looking to learn more about (or brush up on) machine learning should check out this free resource we’ve discovered. The blog over at Conductrics supplies what amounts to a partial syllabus for self-study in “A List of Data Science and Machine Learning Resources.” The article shares links to websites that address each of several topics.
Writer Matt Gershoff introduces his resource roster:
“Every now and then I get asked for some help or for some pointers on a machine learning/data science topic. I tend to respond with links to resources by folks that I consider to be experts in the topic area. Over time my list has gotten a little larger so I decided to put it all together in a blog post. Since it is based mostly on the questions I have received, it is by no means complete, or even close to a complete list, but hopefully it will be of some use. Perhaps I will keep it updated, or even better yet, feel free to comment with anything you think might be of help.”
There is one caveat: Gershoff explains that, since machine learning is his thing, he hasn’t included anything on hardware or coding in this list. He recommends that, if your matrix (linear) algebra is rusty, you start with MIT’s undergraduate Linear Algebra class, available for free as video lectures by Professor Gilbert Strang. After that, it’s on to general machine learning with what Gershoff considers the most valuable link in his post—the machine learning page at VideoLectures.net.
The article goes on to suggest several more useful links. For example, one lecture contrasts Bayesian and Frequentist classifications, another source tackles deep learning, and yet another covers natural language processing. Check it out to boost your data science skills.
Cynthia Murrell, January 21, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
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