DescriptionMachine learning (ML) is the science that explicitly enables computers to act without being explicitly programmed. It is the most dominant tool that has the potential to mimic the human brain and thus used as a cutting edge technique in Artificial Intelligence. In this course, we dive into the fundamentals of ML and gain some insight on its implementation by actually hand-coding some practical algorithms. The content of this course (4 lectures) is designed for beginners, not only for them to grasp the theoretical concepts quickly, but also to gain the practical know-how of its implementation on some real-life problems. This course provides a broad introduction to machine learning and introduction to TensorFlow as a tool to solve practical problems. You need to attend following sessions to get the credits: 1/4: 10 Jan 2021 9:30 - 11:00 AM AT 2/4: 11 Jan 2021 9:30 - 11:00 AM AT 3/4: 12 Jan 2021 9:30 - 11:00 AM AT 4/4: 13 Jan 2021 9:30 - 11:00 AM AT
Dr. Naeemullah Khan received his masters and Ph.D. degrees from Kaust in 2014 and 2018 respectively, in Electrical Engineering. Since 2018 he has been part of the Torr vision group (TVG) at the department of engineering, the University of Oxford. The primary focus of his research is the theoretical evaluation of deep networks. He has also been involved in several courses and summer schools on machine learning at artificial intelligence at the University of Oxford.
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