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. Qamar currently works as a System Modeling Specialist at KAUST for Water Desalination and Reuse research center. He has vast experience in predictive computational and analytical modeling, numerical and statistical methods, data and qualitative analysis, large data visualization, visual analytic, high-performance computing on clusters and supercomputers. He has been actively involved in cutting-edge data science and modeling research with impactful outcomes.
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