A few weeks back one of my children flushed an unknown item (toy or something) down one of the toilets. Well, it caused some problems, and the toilet was not working properly. So, I did what any reasonable person in 2012 would do. I googled for plumbers in my area and called one of them. I happened to call Mr. Rooter Plumbing Service. They came the next day and fixed the toilet.
Great Ryan, What does this have to do with data science?
Well, the following week, I started seeing this add.
I no longer needed a plumber! The process that determines what adds I see is definitely a data product. The problem is the solution is too slow. By the time the add company has figured out what I need, I no longer need it.
This just reminded me of why data science needs to focus strongly on real-time or near real-time solutions. Our world moves quickly and the data products need to respond accordingly. Are you aware of some good work being done for real-time data science? I know it is out there.
In the end, I would recommend Mr. Rooter, but I would wait for the coupon first.
Yesterday, Coursera announced that students will soon be able to earn college credits for some of the courses. See the blog post with the college credit announcement.
In case you missed my slides I posted this weekend, the end of the presentation mentions a new project I am starting to create. It is called Data Science 201. The goal is simple:
To be the best place on the web for learning about all topics in data science
Blogging is great, but there is more data science resources on the internet than I could ever read/evaluate and blog about. That is why I am creating Data Science 201.
Don’t worry, I will keep this blog going.
These are some slides from a talk I gave at South Dakota Code Camp. I also could have titled the presentation, “How to Learn Data Science.”
Also, the slides contain lots of links to other resources. Enjoy!
Strata Conference/Hadoop World NYC 2012 videos are now available on Youtube. All the videos are not there, but most of the keynotes and some extra interviews are available.
Cathy O’Neil(on the right) provides some great details about why it is difficult to teach data science in college. She also mentions that some of the best people to lead data science programs are probably not publishing papers. They are working in industry.
Microsoft has been doing machine learning for a long time, and it looks like some of those efforts might soon pay off. How do you think this will work out for Microsoft?
Microsoft Renews Relevance With Machine Learning Technology – NYTimes.com.