A key part of the scientific method is communicating the insights to an audience, for any field of research or problem context. This is where the ultimate value comes from: by sharing the cutting-edge results that can improve our understanding of the world and help deliver new innovations in people's lives. Effective science communication sits at the intersection of data, research, and the art of storytelling. In this episode of the DataCafé we have the pleasure of welcoming Laurie Winkless,...

Culture is a key enabler of innovation in an organisation. Culture underpins the values that are important to people and the motivations for their behaviours. When these values and behaviours align with the goals of innovation, it can lead to high performance across teams that are tasked with the challenge of leading, inspiring and delivering innovation. Many scientists and researchers are faced with these challenges in various scenarios, yet may be unaware of the level of influence that...

Do you have multiple devices connected to your internet fighting for your bandwidth? Are you asking your children (or even neighbours!) to get off the network so you can finish an important call? Recent lockdowns caused huge network contention as everyone moved to online meetings and virtual classrooms. This is an optimisation challenge that requires advanced modelling and simulation to tackle. How can a network provider know how much bandwidth to provision to a town or a city to cope with...

Do you ever find yourself wondering what the data was you used in a project? When was it obtained and where is it stored? Or even just the way to run a piece of code that produced a previous output and needs to be revisited? Chances are the answer is yes. And it’s likely you have been frustrated by not knowing how to reproduce an output or rerun a codebase or even who to talk to to obtain a refresh of the data - in some way, shape, or form.  The problem that a lot of project teams face, and...

Are people resistant to change? And if so, how do you manage that when trying to introduce and deliver innovation through Data Science? In this episode of the DataCafé we discuss the challenges faced when trying to land a data science project. There are a number of potential barriers to success that need to be carefully managed. We talk about "change management" and aspects of employee behaviours and stakeholder management that influence the chances of landing a project. This is especially...

Data scientists usually have to write code to prototype software, be it to preprocess and clean data, engineer features, build a model, or deploy a codebase into a production environment or other use case. The evolution of a codebase is important for a number of reasons which is where version control can help, such as: collaborating with other code developers (due diligence in coordination and delegation)generating backupsrecording versionstracking changesexperimenting and testingand working...

We explore one of the key issues around Deep Learning Neural Networks - how can you prove that your neural network will perform correctly? Especially if the neural network in question is at the heart of a mission-critical application, such as making a real-time control decision in an autonomous car. Similarly, how can you establish if you've trained your neural network at the heart of a loan decision agent  with a prebuilt bias? How can you be sure that your black box is going to adapt to...

The grey, green and yellow squares taking over social media in the last few weeks is an example of the fascinating field of study known as Game Theory.  In this bite episode of DataCafé we talk casually about Wordle - the internet phenomenon currently challenging players to guess a new five letter word each day. Six guesses inform players what letters they have gotten right and if they are in the right place. It’s a lovely example of the different ways people approach game strategy through...

Looks like we might be about to have a new Series of DataCafé! Recording date: 15 Feb 2022 Intro music by Music 4 Video Library (Patreon supporter)

Data Science in a commercial setting should be a no-brainer, right? Firstly, data is becoming ubiquitous, with gigabytes being generated and collected every second. And secondly, there are new and more powerful data science tools and algorithms being developed and published every week. Surely just bringing the two together will deliver success... In this episode, we explore why so many Data Science projects fail to live up to their initial potential. In a recent Gartner report, it is...

What's the difference between a commercial data science project and a Data Science project for social benefit? Often so-called Data Science for Good projects involve a throwing together of many people from different backgrounds under a common motivation to have a positive effect. We talk to a Data Science team that was formed to tackle the unemployment crisis that is coming out of the pandemic and help people to find excellent jobs in different industries for which they have a good skills...

The scientific method consists of systematic observation, measurement, and experiment, and the formulation, testing, and modification of hypotheses. But what does this mean in the context of Data Science, where a wealth of unstructured data and variety of computational models can be used to deduce an insight and inform a stakeholder's decision? In this bite episode we discuss the importance of the scientific method for data scientists. Data science is, after all, the application of...

Mars 2020 is the latest mission in the exploration of Mars and landed the Perseverance rover in February 2021 with the goal of obtaining new data about Mars and demonstrating the technology to do it.

How to hire a great data scientist who has the right balance of skills and behaviours to complement your company or team.

Bayesian inference encourages us to update our model from our prior belief as new data becomes available.

A case-study for contextual bandits and reinforcement learning algorithms.

Optimising the Future: learning from past data to minimise the unknowns of the future.

What exciting data science problems emerge when you try to forecast an election? Many, it turns out!We're very excited to turn our DataCafé lens on the current Presidential race in the US as an exemplar of statistical modelling right now. Typically...

What are solar storms? How are they caused? And how can we use data science to forecast them?In this episode of DataCafé we talk about the Sun and how it drives space weather, and the efforts to forecast solar radiation storms that can have a massive...

We talk to Freddie Odukomaiya about his journey from data science to entrepreneurship following the Lean Startup approach.

What is a virus? How can we spot human viruses in danger of becoming pandemics? How can we use statistics to understand their origins and transmission? This turns out to be a hard problem - not least because there can be many hundreds or thousands of...

Changepoints: the secret weapon of the data scientist

Inventory Optimisation is the science of maintaining sufficient stock levels and availability to customers.

Vehicle Routing Problem (VRP) is the optimisation problem that describes all manifested delivery operations.