My first introduction to the Julia language, was mentions at R or Python events, that “the cool kids are writing in Julia these days“. Now, bloggers are always in danger of being on the look out for something topical or trendy, but further investigation revealed that Julia is indeed a useful language with growing usage amongst data scientists.
So, to ensure we are not limited to the more familiar R and Python languages, I’m delighted to extend our series to also look at resources for Julia programmers, or those wanting to consider this language. As before, I’ll share a book recommendation for learning Julia, as well as some online resources, cheat sheets and an event to attend.
I hope this proves useful, for Data Scientists and Insight Leaders, who are seeking to expand their repertoire or achieve better performing code.
Although R may have a longer heritage within the Statistics and Data Science community, Python could be described as a more complete programming language.
In my conversations with clients and Data Science leaders, I’ve also heard a number praise Python as much quicker to learn. So,although both languages are proving popular with analytics teams, there is perhaps a choice between the more statistically grounded R and the easier programming in Python.
But, even that distinction is now less clear, as both benefit from the kind of support/resources ecosystem that I mentioned in my post on R.
So, enough introduction, let me share some resources that I’ve found to help Python coders (and would be coders). Enjoy diving in, at the risk of getting bitten by the coding bug. (more…)
In the past I have tended to avoid these programming languages as a topic for this blog, as I have some concerns. Namely that the role of insight analysts, in the migration to job title of Data Scientist, is being reduced to that of a programmer. Too much focus on coding skills & the capabilities of new packages, can reduce the needed focus on interpretation, insight generation & influencing a business.
However, working with clients, I am seeing that a majority are now embracing this new generation of analytics tools/languages. So, I thought it would make sense to (hopefully) help readers by sharing the resources I have found online for a few of the most popular options.
In this post we will focus on the R programming language. (more…)
During our month with more focus on Data Visualisation, we should not overlook data visualisation books.
I hope our previous posts, focussing on Data Viz blogs and twitter experts have helped your personal development. But, even in this digital age, we should not overlook the power of books.
Whether you invest in hard copy or digital versions, the longer form of books often gives opportunity to better structure information for self-development. So, to complement those earlier resources, in this post I am going to recommend a number of books from 9 experts. (more…)
When I first received a copy of this book, when it was published in 2014, I didn’t think it would be so relevant. Understanding a ‘mobile mind shift‘ sounded like just a fancy way of presenting advice for e-commerce leaders working on moving to mobile.
Now, having read this engaging work, I can see how relevant it is to all business leaders (including customer insight leaders).
There is much more to think about than you might first imagine. This practical book makes a good case for explaining why you can’t just port your website. It’s also much more involved than just having a dynamic presentation layer, that will adapt to the device (i.e. screen size) being used. (more…)