Teaching Artificial Intelligence with MATLAB

Overview

Educators teach deep learning with MATLAB by drawing on available course modules, onramp tutorials, and code examples. With domain-specific toolboxes and apps, MATLAB makes it easy for students to learn and perform domain-specific deep learning tasks involving data preprocessing, image labeling, network design and transfer learning.

MATLAB supports interoperability with open source deep learning frameworks, enabling students to apply TensorFlow, PyTorch, and other popular frameworks in their MATLAB deep learning projects.

Using MATLAB students can combine statistics and machine learning with application specific techniques such as signal processing, image processing, text analytics, optimization and controls.

About the Presenter

Souvick Chatterjee, Educational Technical Evangelist, MathWorks:

Souvick Chatterjee is currently an Educational Technical Evangelist at MathWorks India Pvt. Ltd. Souvick completed B.E. in Mechanical Engineering from Jadavpur University in 2009, after which he joined a M.S.-PhD program between Jadavpur University and Virginia Tech. He is recipient of Best PhD Thesis Award and Young Scientist Award from International Society for Energy, Environment and Sustainability. He worked in University of Illinois at Chicago as postdoctoral associate. He has co-authored 14 journal articles, 2 book chapters and is co-inventor of 2 US patents. He also worked as commercialization consultant to assess market potential of innovative university technologies like water filtration, machine learning based application for early diagnosis of bipolar disorder. His academic experience taught him the power of computational thinking and model-based product-oriented interdisciplinary and integrated approach in research and education. In his current role in MathWorks, he is advocating this approach partnering with universities across the country.

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