Data Science: K-Means Clustering in Python

Dr. Betty Fyn-Sydney is a pure mathematician and associate lecturer in Mathematics at Goldsmiths, University of London, where she has been teaching since September 2016. In addition to her role at Goldsmiths, she serves as a teaching fellow at the University of Birmingham and a lecturer at Greenwich University. Her research focuses on group theory, representation theory, and coding theory, highlighting her commitment to advancing the field of mathematics. Dr. Fyn-Sydney conducts tutorials and workshops on various subjects, including Foundations of Problem Solving and Mathematical Modelling, while supervising undergraduate projects at Birmingham and leading tutorials at Greenwich. Her teaching experience spans modules in Linear Algebra, Group Theory, Number Theory, Calculus, and Statistics.

Dr. Matthew Yee-King is a Lecturer in Computing at Goldsmiths, University of London, specializing in creative digital signal processing and computer music. He has collaborated with prominent figures in the UK experimental music scene, contributing to the advancement of innovative sound technologies. In his teaching, Dr. Yee-King covers a range of topics within the BSc Creative Computing program, including audio signal processing and synthesis, programming in Processing, and audio development for the Android platform. His expertise not only enriches the academic experience for students but also fosters a deeper understanding of the intersection between technology and artistic expression. Through his work, Dr. Yee-King continues to push the boundaries of how digital tools can enhance creative practices in music and sound design.

Dr. Jamie A. Ward is a Lecturer in Machine Learning at Goldsmiths, University of London, where he has been teaching since December 2018. He also holds visiting positions at the Institute of Cognitive Neuroscience (UCL), Keio University in Japan, and the German Centre for Artificial Intelligence (DFKI) in Kaiserslautern. Dr. Ward earned his Ph.D. from ETH Zurich in 2006, focusing on wearable sensing for human activity recognition, and later worked as a Marie Curie Research Fellow at Lancaster University, developing methods to use eye movement for activity inference. After a brief hiatus to pursue acting, he returned to academia in 2017 and has since co-led two European Research Council (ERC) projects: Neurolive, which investigates the neuroscience of live performance, and SocSense, aimed at measuring social engagement in autistic children. Dr. Ward is actively involved in the academic community as a member of the steering committee for the International Symposium on Wearable Computing and serves as an associate editor for IEEE IMWUT. His interdisciplinary research combines elements of neuroscience, wearable technology, and theatre, contributing significantly to the understanding of social interaction and activity recognition.

Dr. Larisa Soldatova is a Reader in Data Science at Goldsmiths, University of London, where she has been the Programme Convenor for the online MSc Data Science since November 2017. With nearly 20 years of experience teaching Data Science modules to undergraduate and master's students, she also supervises final year projects, MSc, and PhD dissertations. Dr. Soldatova is internationally recognized for her expertise in Artificial Intelligence (AI) and its applications within the Life Sciences. She has led several international research initiatives, including the European project AdaLab (2014-2018), which focused on AI applications for automated experimentation and systems biology. Additionally, she has been involved in the high-profile Robot Scientist project for over 15 years, which achieved the first-ever automated scientific discovery. Dr. Soldatova co-leads the ACTION project on cancer (2017-2021), funded by the Engineering and Physical Sciences Research Council (EPSRC) in the UK, aimed at developing a decision support system for cancer treatment that performs comparably to human oncologists. Her research contributions have been published in prestigious journals such as Science and Nature Biotechnology, underscoring her significant impact on the field of data science and AI in healthcare.