Machine Learning

Automated image and data clustering

We are excited to introduce our new feature – Automated image and data clustering! Besides offering a fascinating representation of the data, it provides some immediate practical benefits such as efficient labelling and rapid outlier detection.

Stronger Together interview with Microsoft

In this interview with David Smith, Developer Advocate at Microsoft, our CEO Roger Noble explains how Zegami collaborated with the University of Oxford to analyse a research database of lung X-rays, and develop a machine learning model to identify cases of COVID-19.

Roger Noble and Steve Taylor interviewed by Oxford Investment Consultants

Join OIC Principal and CFO Tania Wilson interview our CEO Roger Noble and CSO Steve Taylor.

Case Studies Hero

Data firm Zegami joins project to find cure for ME

Zegami, the Oxford University data visualisation spin-out, has joined an international team of medical researchers to try and find the

Webinar: Analysing X-Rays For COVID-19 Using AI

13th May, 11:00-11:40 BST Zegami has built a tool that could help speed up diagnosis of COVID-19, using a combination

Using AI to speed up COVID-19 diagnosis

Zegami has developed a new machine learning model using x-rays of Covid-19 infected lungs, artificial intelligence techniques and data visualisation tools that could help medical professionals identify corona virus cases more effectively

Colour By Column in Zegami

Our new Colour by Column feature is a powerful new dimension to visual data exploration in Zegami, enabling richer views, which reveal more of the underlying patterns in your data.

Oxford’s MRC Weatherall Institute for Molecular Medicines Partners with Data Visualization Firm on Machine Learning

Zegami has been collaborating with MRC Weatherall Institute for Molecular Medicines to help clean its data and assist with the training of its machine learning models, specifically around developing a better understanding of which proteins in genes bind, and where they do this in the genome.

Can you see the blind spots in your machine learning?

Looking back at the pace of innovation over the last 10 years it becomes increasingly difficult to imagine a world

Hyperparameter tuning with Zegami

Reinforcement learning is a type of machine learning often applied to problems involving indirect rewards – that is, in which

Harnessing the data tsunami

When it comes to both business and research, having more data ought to mean having more information, which should in

Machine learning ‘causing science crisis’

The recent post about the reproducibility crisis in science is, to someone who works in science, not big news. Difficulty