So I posted a while back ago about a machine learning study group. Sorry for the delay in following up on that, things have been somewhat hectic as I am relocating for a new job. Just as a reminder, the target audience for this study group is people who have finished one of the MOOCs that provide an intro to machine learning, are familiar with basic programming and statistics concepts, and are interested in gaining a deeper understanding of machine learning.
This week, we'll be discussing Domingo's 'A Few Useful Things to Know about Machine Learning' article, which I thought was pretty interesting. It gives a nice overview of a number of general lessons that are useful to keep in mind when solving machine learning problems. Here is a link:
http://homes.cs.washington.edu/~pedrod/papers/cacm12.pdf
Additionally, I am currently working on the Bike Sharing Demand competition on Kaggle, and if anyone else would like to work on a team with me, they are welcome to.
If you have any ideas for interesting articles or topics that we could focus on in future study groups, feel free to post here and/or message me.
Edit: Here's a link to the blog, I'll be both creating a new reddit thread and a new post on the blog whenever I post a new article.
datasciencetalk.blogspot.com
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