Sunday, January 17, 2016

R and Python


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18 January 2016: Building Machine Learning Systems With Python eBook- Grab it free while offer runs out in less than 21 hours! Kindle version, not free (affiliate link) is also available on Amazon, though to be honest, unfortunately the reviews are not too positive.

Read more here about Python vs R for machine learning.

For jobseekers who gravitate towards Machine learning, here's Udacity's Nanodegree Plus - Machine Learning - Get hired guaranteed, conditions apply.




In my previous post on learning a new programming language: Python,  Data analyst is mentioned or recommended.

Programming had progressed and become more complex over the years, may no longer be just about compiling a COBOL file and expects an simple output or just Msgbox(), lists and writing to database in Visual basics. It can still be but more people are looking for more than one skill set to filter out the applicants, understandably and sadly so. I may be wrong, there were challenges and hardships in the past, modern times too has its list of it - some overlapping and new I suppose. People are expected to know so much more before they will be considered for intermediate , higher position.

Nowadays, to be a decent a programmer, in my opinion, one may have to dabble in a few technologies to be proficient. For example, writing and sharing decent projects on Github, and then perhaps deploying them on another platform can be a an important and direct way to telling employers or clients what you had done. Another example is the the use code editors or IDE, in order to be a coder, one most likely has to be familiar with certain code editor of his preference, even testing and configuring for one that works and satisfy his requirements can be time-consuming before even beginning to code. Of course, some may just prefer to just code in basic notepad/Vi/Emacs. So far, my choice is Atom editor and SublimeText could be my next best choice. Online editor, I would recommend giving Cloud9 a shot.

While learning Python, R kept popping up while browsing the websites. Basically, R programming seem 'tailored and focused' on data analysis. Python is a general purpose, syntactically clean language that can also do data analysis e.g. Pandas, but looks like R is so geared towards mathematics, statistics and existing packages for this purpose. More here on Quora if you are interested.

Should you learning R, python or both?

I guess it all depends on what you want to accomplish. Say for example, if you just want to get hired to do Machine Learning, then you might as well enroll in Machine Learning Engineer Nanodegree Plus, which may not focus solely on R. If you are mathematically competent with a curious tendency to focus and explore data and graphs, then R programming can be your playground. I would think a coder who may have a general interest in programming, unsure about what his future or interest, then Python can be a good choice that can develop in different directions, ranging from web development, data analysis to database administration. Of course, those with the aptitude can do both, then again, consider if you are overloading and distracting yourself from being skilful in one, especially for a novice programmer. Or learn R after Python. To each his own.

Personally, I like to research and map out what are the possibilities and where it goes. I prefer Python official site's design, outlook and content to R-project website for one.





Above are two graphs to help understand how Python and R compare under development tools.


Conclusion


If you ==  mathematically or statistically inclined towards data analysis or machine learning:
    Learn R and/or Python
else:
    Learn Python


In any case,  if you wish to learn more about R programming, below can be good courses or resources to get you started.

Courses


Free and paid: 13 R programming related courses - Datacamp

Free -  R Basics - R programming  introduction - Udemy

Free - Data Analysis with R - Udacity

Be kind and best wishes.

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