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Ask HN: Do any of you do data science as a hobby?
I work in mergers & acquisitions (math major undergrad, Python classes) but enjoy looking at interesting financial and non-financial datasets in what little free time I have.
What project(s) have you worked on? Can a self-taught hobby data scientist produce solid/meaningful statistical analysis/results products?
- minimaxir 9y agoWhile working as a Software QA Engineer at Apple, I wrote a large amount of statistical blog posts to get a breadth of skills outside of my role (story: http://minimaxir.com/2017/05/leaving-apple/ http://minimaxir.com/2017/05/leaving-apple/) I did have a statistical background before starting at Apple however. Most of my projects were self-taught and done as self-research (I am not a fan of the take-a-million-MOOCs strategy everyone likes).
- RealAnalysis 9y agoThanks for the link! I'm mostly interested in self-research. How'd you know you were doing sound stats?
- usgroup 9y agoOh that's easy ... put money on it, it'll make you a better statistician in no time.
- cuchoi 9y agoWith a team of data-scientists-as-a-hobby, we are building www.17-56.cl, which displays insights from data about Chile. It is in Spanish, but feel free to look around. For example, I created a map that displays the votation in the Chilean primary elections: http://fernandoi.cl/mapascomunales/primarias/primarias.html http://fernandoi.cl/mapascomunales/primarias/primarias.html. Simple, but informative and fun. Probably as a hobby you will not be able to write an analysis that will get published in a paper, but there is a lot of descriptive analysis out there that can be very interesting.
- RealAnalysis 9y agoHow do you know your statistical analysis is good? I'm rereading my intro to stats book and would like to use those skills to make good analysis.
- cuchoi 9y agoIt depends on the type of analysis you are doing. It is very difficult to generalize. If you are looking for causation, I would say to not even try it unless you are writing a paper.
- ivm 9y agoAwesome, I saw that we have so much data published by the government but it was always buried in endless spreadsheets. Thanks for working on this!
- cuchoi 9y agoYes, it is mostly government data! Also, this year there are presidential election in Chile so there is a bias towards that topic.
- eb0la 9y agoI really like it :-) Never underestimate descriptive analysis. After all, that's the first step you take before digging further in the data.
- RealAnalysis 9y agoI'm really just wanting to do my own self research on topics and datasets that seem interesting, but also want to ensure the analysis im doing is sound.
- usgroup 9y agoLearn to cross validate. Typically by predicting something out-of-sample. Or by sense checking what your model says about things you're sure about.
- gesman 9y agoBuilt model + app (Splunk app) to predict medicare and opioid prescription fraud based on published medicare claims datasets at data.cms.gov
- jklein11 9y agoHow did you know which claims were fraudulent?
- thenomad 9y agoYup, from time to time. I also use data science in one side of my business (online marketing), but as a hobby I periodically do data analysis of the computer game DOTA2. There's a large (huge, actually) available dataset, and lots of interesting information you can mine comparatively easily.
- SirLJ 9y agoAbsolutely, been doing it for years with stock market data and Python - developing trading algos and very successfully I might add, actually I can retire tomorrow, but every year I am postponing, because of the team I lead...
- riku_iki 9y agoMy project is https://finintelligence.com https://finintelligence.com It provides access to public/private companies financials, documents search and some custom reports. I have tons of ideas in my mind: configurable stream of companies events, alerts, intelligent search for companies data, etc. I launched it just about a month ago, so it is still in a semi-stealth prototype mode, but I am happy to receive any feedback, feature requests and first real users )
- navalsaini 9y agoI like doing data science courses for fun. These days I am reading CS 229 mathematics and a book Python Machine Learning. Once in a while I get tired of coding in JS, or adding things to side projects; and then I like doing simple learning, just for the sake of learning and trying to understand (no strings attached). I like the maths part of data-science and maybe would pursue it as a theoretical endeavor. Or just repeat what people have posted on GitHub and see the results - like kids soldiering circuits. It would be fun to take part in some Kaggle competitions next year, around healthcare. Back in 2014, I spent some time working on an SVM classifier for news.