We’re often bombarded with how popular data science is as a career. It’s all too common to read things like data science being the “Sexiest Job of the 21st Century” or yearly comparisons of high salary expectations.
Data science has a lot to offer. It’s a challenging role with plenty to learn and keep you occupied. Compared to many other roles, data scientists can be given a lot of autonomy to explore and solve interesting problems. And, in many cases, you’ll get the opportunity to work with talented and skilled people in a variety of domains.
More than anything else, how you communicate will be the dominant factor in your success as a data scientist. Hear why and what you can do to turn communication into a strength.
I get asked a lot by aspiring data scientist questions about how to improve and what they should be focusing on. Things like:
While these are all valid things to be considering (in the right context) for the vast majority of people they’re not where you should be focusing…
I first started coding during an extended hospital stay back in 2010. I told myself, “If I’m stuck here, I want to learn something useful.” Like most people who take the plunge, I soon got carried away with this newfound power! Even the incredibly simple things I was able to do in C++ opened my eyes to the possibilities and wonder of it all.
I was first introduced to machine learning during my Ph.D. I was researching tools and techniques for optimisation in high-powered laser defence systems and stumbled upon reinforcement learning. …
Data science is a highly attractive career for many reasons — so the competition can be tough. Some of the tips below that make a great candidate stand out might surprise you!
I’ve written this article for a variety of audiences:
This is a question I often get at user groups and community events for aspiring or…
Get started with persisting data and state when working with data science containers. A guide to data storage and persistence in Docker.
In this post, we’re going to cover data persistence in Docker and how to get your images to interact with data outside of the container. If you’re familiar with Docker or have already walked through the previous posts in this series skip to the next heading!
So far in this series, we’ve covered how to get a basic Hello World! web app built using Flask and Python and deployed using Docker. In Part 2 we walked through an…
If you’re already using Docker for your data science projects, then great —you might now want to learn how to manage and share your containers privately. This post will show you how to get a private repository up and running in Azure.
For this tutorial you’ll need to the following installed:
If you’re not sure where to start with Docker I’ve written two-part series covering getting up and running, then deploying an end-to-end machine learning service in these two posts:
Part one walks through how to get…
How Deepfakes and AI could start to become more common in the media we consume.
As a brit, on Christmas Day I was quite happy to hear the call out for diversity and the nod to all those who have struggled through this year — especially those on the front line in key worker roles and in the NHS.
As a data scientist, I was very interested in seeing Channel 4’s alternative Queen’s Speech. As I’m sure many of you have, I’ve followed the GAN/Deepfake progress for a while now. …
In Docker for data scientists — Part 1 we covered some of the basics around using Docker and got a simple Hello World! example up and running. If you missed that post and want to run through the code, you can find it here:
Our aim in this post is to move on to an example of how a data scientist or machine learning engineer might want to use Docker to share, scale, and productionise their projects.
We’ll work our way through the following topics:
We’re going to jog through the following topics in order:
Over my time working in data science I’ve seen many people struggle with (or simply ignore!!) the concept of environments.
With tools like
condamaking it easy to install packages and libraries on the fly, it can be very tempting to just download everything you’ll ever need into the default environment and be done with it. Things will work fine for…
Dr Adam Sroka, Head of Machine Learning Engineering at Origami Energy, is an experienced data and AI leader helping organisations unlock value from data.