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Do anybody know about a github repo with a full well organized data science project? Preferable in Python. My hobby project often get mezzy with a mix of Python code and notesbook. A worked out project is the best way to learn some new tricks.
Data Science is regarded a bit differently by different people, so you might consider focusing on what exactly you wish to learn.
But, take a look at those:
https://github.com/bulutyazilim/awesome-datascience
https://www.kaggle.com/
The first one contains lots of relevant sources of information. The second is originally a competition site with varied different problems in ML, but also contains past competitions (and datasets). They added a cool feature called "kernels" which are just code files people publish and you could learn from those.
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I've just started reading How to Design Programs (2nd edition) on htdp.org
There are several notes in this book mentioned next volume called How to Design Components (e.g. the 3rd note in part one), however, I just can't google anything about the 2nd volume book.
I'm wondering why it is so hard to find any information about the latter volume. Has it finished? If it has not finished yet, how can I get information about the book?
The first author provides more information on his website:
We have decided to provide the draft of "How to Design Classes" (pdf)
on an "as is" basis for now. You are free to download and print it.
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I am building a path for beginners (like me) to guide them through the learning of data analysis in R (Only in R please).
Would you suggest me any new sections and/or new courses that i should add?
Heres is what i have been adding till now: http://studiy.co/path/data-analysis/
Thanks for the help!
well you need to distinguish... If you want just to learn R programming you may check Coursera course on R
https://www.coursera.org/learn/r-programming
that would give you some basics. If you need to learn how to analyse data then you may need a bit more. What are your background in mathematics? What kind of statistics know-how do you have? A GREAT resource in my opinion is the book
An Introduction to Statistical Learning with applications in R
That you can even find for free in pdf (http://www-bcf.usc.edu/~gareth/ISL/). Beware that you may need some mathematics background to be able to understand it fully. In case you have a more profound background in science I may have other suggestions. Could you tell us at what level are you?
Hope that helps.
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I have been trying to find a program that can extract information from unstructured text(news articles, books, etc).
My eventual goal is to create a program that can take regular sentences and cache it in a database much like google does but without all its duplicate information.
lets take the NLTK example: "At eight o'clock on Thursday morning Arthur didn't feel very good."
the things that i would want extracted would be:
time: 8:00pm
date: thursday
person: Arthur
action: didn't feel good
is there a program that can do this?
i have tried using NLTK but i cant seem to find any good way to accomplish extracting the information.
This problem is called Fine grained entity recognition. No, There are no tools (except for research works) that can add such semantics.
To start with, you can recognise Person and Time with appropriate models using Entity Recogniser.
You can recognise the actions from sentence parsing as suggested by #Junuxx.
Also give Wikify a try.
Thank you.
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I have read about 1/3 of the GNU Make manual, do you guys know of any resources to really learn the Art of using Make.
Ideally, there might be some examples where two ways of doing something are possible, and the author explains which method he chose and why.
I am primarily using Make not to build C/C++ programs but to operate a processing pipeline for data analysis.
Managing Projects with GNU Make, by Robert Mecklenburg, is the best I've come across. Plus, it's an O'Reilly Open Book, so O'Reilly gives away free PDFs of it on their website. Read it linearly, and start from the beginning (even if you think you already know the basics of GNU Make).
John Graham-Cumming has written a book called GNU Make Unleashed which looks promising, although I have not read it yet. http://www.lulu.com/product/paperback/gnu-make-unleashed/2937580 and http://jgc.org/
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We are building a "configurator" application for conveyors. Basically user comes in and picks a model, then start picking the parts they want. Some components have dependencies on other components. E.g. if I pick Part A, then I am required to select 1 or more Part B's. It is somewhat similar to configuring a PC at Dell.com. The app will also provide suggestions on parts/components.
Based on this info, I am researching if there is an existing pattern(s) that would allow us to make this easy to maintain and design. Any thoughts, ideas? Are there any open source projects that have similar functionality I can borrow ideas/patterns?
I am mostly interested in how to define "rules" between components without hardcoding the rules/dependencies.
Thanks for any help.
Not that it should matter, but we are building this in .NetFramework 3.5/Asp.Net
Without a good reason to do otherwise, I'd keep it simple and each part would have a list of dependent parts.