Introduction to Excel by Deji Olayinka The field of data science is vast but before diving in it’s key to understand the basics. In this talk, we will discuss the use of Python as the programming language of choice and how its packages can be used to perform some fundamental concepts in data science.
Basic Python Libraries for Data Science by Robert Mastrodomenico The field of data science is vast but before diving in it’s key to understand the basics. In this talk, we will discuss the use of Python as the programming language of choice and how its packages can be used to perform some fundamental concepts in […]
Productionising Data Science by Paul Brabban, Simon Case & Scott Cutts Our engineers help our clients get the most they can from their data. We are going to share some of the techniques we have used to create the data pipelines, productionize the data science, and operationalise Machine Learning. We’ll talk about how we use […]
Join us and see how our team shed a light on the optimality of budget allocation problem with a Reinforcement Learning system that yields recommendations
In this session, we explore how MLOps is deployed to scale ML at M&S across two diverse use cases that span from one-to-one personalisation which serves to enrich customer experiences, to enterprise functions that help M&S run better as a business.
Our vision is to be the UK’s most loved way to eat dinner. We plan to do this by focusing on the customers, ensuring we build a compelling product that understands their needs
In this discussion, we will try to uncover all the possible mysteries and misunderstandings related to the DS field.
This session will cover how you can implement the ML Flow framework to manage your model development process end-to-end, have a complete view of the models you have been training, and how you can structure a production-grade model deployment strategy.
Accelerating data-intensive ML applications with the Graphcore IPU by Tim Santos Traditional processing architectures for data science and machine learning are hindering where the industry can go next in Machine Intelligence. New hardware is required to run complex ML models and handle large-scale data workloads. This talk will outline how Graphcore’s IPU architecture and Poplar® Software Stack […]