Maths in a minute
Want facts and want them fast? Our Maths in a minute series explores key mathematical concepts in just a few words. From symmetry to Euclid's axioms, and from binary numbers to the prosecutor's fallacy, learn some maths without too much effort.
Have you ever noticed the strange phenomenon of wheels appearing to move backwards while the vehicle is moving forwards? Aadit Jain explains why!
Machine learning started with supervised learning and us providing all the training materials, but we are finding ways for algorithms to learn with far fewer resources.
A quick look at one of the most important theorems in number theory.
Whether you're lost on a mountainside, or training a neural network, you can rely on the gradient descent algorithm to show you the way!
Machine learning makes many daily activities possible, but how does it work?
If you love triangles as much as we do, we have great news – you can have them in any dimension you want!
When trying to build an artificial intelligence, it makes sense to mimic the human brain. Artificial neurons do just that.
How do you calculate your risk of catching an airborne disease?
The mathematical equations governing fluid flow may have no known solutions, but maths still has the answers!
When you receive a positive test result for a disease, the chance you actually have it depends on how common the disease is.
When things go round and round, a cyclic group may be just what you need!
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Want facts and want them fast? Our Maths in a minute series explores key mathematical concepts in just a few words.
The BloodCounts! project is gearing up towards one of the largest-scale applications yet of machine learning in medicine and healthcare.
What do chocolate and mayonnaise have in common? It's maths! Find out how in this podcast featuring engineer Valerie Pinfield.
Is it possible to write unique music with the limited quantity of notes and chords available? We ask musician Oli Freke!
How can maths help to understand the Southern Ocean, a vital component of the Earth's climate system?
Was the mathematical modelling projecting the course of the pandemic too pessimistic, or were the projections justified? Matt Keeling tells our colleagues from SBIDER about the COVID models that fed into public policy.