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I had a colleague who is using Xilinx's LocalLink TEMAC
While I find the DS interesting, I would like to learn more about the basics of it. Does anyone have any recommendations for a good low-level intro to networking/ethernet book?
I don't need to know "how to be a good network administrator", but rather interfaces like the MII, GMII, and how they communicate with different PHYs that are on the market. My questions that I'd like to learn about are similar to:
What is ethernet?
How are packets structured?
What is a preamble and how is it used?
What is a frame?
I'd also be interested in online sites if it's really much easier to learn from in your opinion. If there is a book series, I would be open to that as well.
One of the best networking books I've found is "The TCP/IP Guide: A Comprehensive, Illustrated Internet Protocols Reference" http://www.amazon.com/TCP-Guide-Comprehensive-Illustrated-Protocols/dp/159327047X/ref=sr_1_5?ie=UTF8&qid=1312296674&sr=8-5. The only thing this doesn't cover in great detail is the actual layer 1 stuff. Well even then it goes over some basic details, but the book is excellent for most anything you need to know regarding networks, packets, headers, etc....
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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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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 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 was given the task to create statistical reports and integrate them to an asp.net application (Webforms) connected to a MySQL DB.
I was looking at this question. However, the accepted answer is about SQL Reporting Services (I am using MySQL), and the most voted answer lists different tools (Crystal, ActiveReports, XtraReports Telerik, Versareports) but suggests they are all evolving and it was in 2009.
So, what options do I have at the present? Which one would you recommend me? Why?
If you want the quick and dirty, easy to use, and fairly flexible option, then ActiveReports still gets my vote. The most extensive is Crystal, but you have to really need the extra bang to warrant it's use, at least IMO. Telerik fits in between (if you are really familiar with their other UI controls, it is not a bad option, however, as the learning curve is greatly shortened).
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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/