Deep Learning with MATLAB: A Visual and Intuitive Approach
Deep Learning with MATLAB: A Visual and Intuitive Approach
The field of deep learning is rapidly gaining traction in various domains and applications, and it has become increasingly crucial for both students and educators to adopt this technology to tackle complex real-world problems. MATLAB and Simulink are powerful and flexible platforms that enable the development and automation of workflows related to data analysis, deep learning, artificial intelligence, and simulation across a wide range of industries and domains.
This presentation aims to introduce the audience to deep learning using MATLAB. During the session, we will construct a neural network from scratch and customize a pre-existing network using the MATLAB Deep Network Designer. This tool facilitates the interactive development, visualization, and training of neural networks, enabling users to fine-tune parameters and generate code for the network. The Deep Network Designer offers users the flexibility to choose between pre-trained networks or create their own, and its visual approach streamlines the workflow, resulting in a more efficient process.
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- Date: 06 Apr 2023
- Time: 12:30 PM to 01:30 PM
- All times are (UTC-05:00) Central Time (US & Canada)
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Speakers
Jon Loftin of MathWork
Deep Learning with MATLAB: A Visual and Intuitive Approach
Biography:
Jon Loftin is a Customer Success Engineer at MathWorks. Jon’s background is in mathematics. More specifically, implementing mathematics in a computer. He holds degrees in mathematics: a BS from Southern Arkansas University, a MS from the University of Arkansas, and a Ph.D. from Texas Tech University. He has had years of teaching experience, from teaching at the Naval Nuclear Power School to teaching as an Assistant Professor. Jon’s research focus is building efficient integration techniques in finite element methods.