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Machine learning is a branch of artificial intelligence in which computational systems learn from their own experiences in order to make decisions. Rather than hardwiring in a system’s responses to inputs, it is designed to work out for itself how to complete certain tasks. The more example data the system is given the better the results will usually be. These systems are especially good at solving problems that would usually require a human brain such as recognising and classifying images, handwriting recognition, facial recognition, natural language processing (understanding spoken and written language including idioms and sentiment, sometimes language translation), self-drive cars, spam email and fraud detection, and medical diagnosis. Despite its representation in popular literature however, machine learning does not really mimic human thought. It is simply used to augment human intelligence and extend our capabilities, often speeding up complex but repetitive tasks or drawing conclusions from data...
Tom has held technical, management and leadership roles in industry and academia. He has published papers, patents and presented internationally in the areas of information technology implementation, machine learning, human performance and genetics, molecular biology, and the autonomic nervous system. He has ongoing professional collaborations with multiple UK and international universities.
Laura holds a doctorate in Particle Physics and GRID computing from the University of Oxford, and Bachelor’s and Master’s degrees in Natural Sciences from the University of Cambridge. She has been a hands-on CTO in medical technologies for a decade, and is an expert at scientific analysis, visualisation and machine learning. She has worked in academia, defence, and as a financial analyst. She has designed and built CE marked medical algorithms and apps.