Last year Louis Columbus of Forbes stated that Machine Learning Engineers, Data Scientists, and Big Data Engineers rank among the top emerging jobs on LinkedIn. David Robinson’s Stackoverflow article about The Incredible Growth of Python substantiates this observation.
Data science in the UK is still emerging, whereas in the US it appears to have taken off in a big way.
It is encouraging to read about mainstream adoption in the UK, even if still early days. The imminent 5G mobile data revolution will fuel the Internet of Things, and will no doubt accelerate and result in a step-change in sources, volume, and variety of data, catapulting data science and associated disciplines into the stratosphere.
It raises exciting prospects. I am thrilled to be part of this and have decided to get more involved. I realise though that, in order to achieve this, I need to participate and contribute more to the ongoing discussion. Thus, I am going to do a lot more online, starting with this website.
I’ve been meaning to create a website for a while now, and recently and unexpectedly got some time to do it. The intention is not to create the world’s best blogging site, but to get a fit-for-purpose web presence as quickly and efficiently as possible.
This website helps me to achieve a few things in particular:
Publish my insights on extracts and highlights from my work in a single and controlled environment.
The more I learn, the more I realise how much I don’t know. I will never stop learning.
Data science and its tools have grown exponentially during the last decade. There is a lot of information available today, and much of it is unoriginal, inaccurate, incomplete, out-of-date or badly written or explained. Also, there are many approaches and tools to accomplish a task, and often it is difficult to choose a way forward.
I have however found many tried, tested and current sources that I continue to draw upon, and which I would like to share and comment on.
I have benefited tremendously from Open Source software, using programming languages like R and Python, in particular the Tidyverse compendium of libraries lead by Hadley Wikham and Pandas by Wes McKinney.
Additionally, there are many altruistic engineers that continue to build on this collaboration, providing free advice through Stack Overflow for example, or free quality education, like Kevin Markham of dataschool in his YouTube series of data science tutorials.
This website allows me to pay it forward.
Some technical blurb about the website
After some research, I have decided to follow the blogdown approach, provided and explained by Yihui Xie. It’s taken me a day to cover basic training and setup and I am really chuffed with the result.
The static website is using the Hugo framework and Beautiful Hugo theme. The source code is pushed to a GitHub repository. The website is hosted on netlify. Netlify automatically pulls the code from GitHub and builds the website. Easy and seamless.
So, hello world! Here it starts with more to follow…