Talk #1 Speaker: Alejandro Saucedo, Chief Scientist at The Institute for Ethical AI & Machine Learning Title: Explainability and bias evaluation in machine learning with Tensorflow Bio: Alejandro Saucedo is a technology leader with over 10 years of software development experience, currently building the Bell Labs of the 21st century as Chief Scientist at The Institute for Ethical AI & Machine Learning. Throughout his career, Alejandro has held technical leadership positions across hyper-growth scale-ups and tech giants including Eigen Technologies, Bloomberg LP and Hack Partners. Alejandro has a strong track record building multiple departments of machine learning engineers from scratch, and leading the delivery of numerous large-scale machine learning systems across the financial, insurance, legal, transport, manufacturing and construction sectors (in Europe, US and Latin America). Twitter: @AxSaucedo
 Talk #2 Speaker: Jakub Langr, R&D Data Scientist at Mudano Title: Towards the use of Graphical Models in business modelling and technology strategy Abstract: Generative Adversarial Networks (GANs) have recently reached few tremendous milestones: generating full-HD synthetic faces, to image compression better than the state of the art to cryptography. In this talk we will start with the basics of generative models, but eventually, explore the state of the art in generating full HD images as presented in https://arxiv.org/abs/1710.10196 Bio: Jakub Langr graduated from the University of Oxford where he also taught at OU Computing Services. He has worked in data science since 2013, most recently as a Data Science Tech Lead at Filtered.com and as an R&D Data Scientist at Mudano. Jakub is a co-author of GANs in Action by Manning Publications. Jakub also designed and teaches Data Science courses at the University of Birmingham and is a Guest Lecturer at the University of Oxford's course "Data Science for IoT". Twitter: @langrjakub; jakublangr.com
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