Learn how R Markdown and Academic can help your team write, collaborate, and publish content online and internally. Examples include a landing page and documentation site for your package, a knowledge sharing platform, or a website for your lab/team.

From mail order to becoming a world class pureplay etailer, we are reimagining retail for our 4 million annual customers. Get insight into how we are leveraging cloud GPUs for deep learning to increase discovery of relevant products and transform how data scientists accelerate research. Learn how we are evolving to embrace microservices to become more agile and foster innovative ways of getting our products, services, and experiences to customers at scale. Finally, what is the future for retail technology and has the time finally come for FPGAs?

After completing his PhD in computer vision and machine learning, George Cushen took a job as the first computer vision data scientist at the UK’s second largest pureplay etailer, Shop Direct. Here, he examines the challenges and parallels between working on academic projects as a computer scientist, and working as a data scientist in a mid-size retail company. Having the opportunity to work within an agile startup-like environment within a well-established business requires breaking the habit of spending hours researching and not getting anything “done”, instead working closely with stakeholders and embracing the scope for innovation in order to create practical products and services. So here are some lessons learnt about the differences between academia and industry and how to make the most out of your academic experience.