Deep Learning Summer Research 2020

Deep Learning (DL)

A friendly introduction to Deep Learning and Neural Networks (33:19)
How Deep Neural Networks Work (24:37)

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Unit 4: Transfer Learning

Due to the size of our training dataset and the limitations of our computing resource, the CNNs we have constructed may not be able to reach...

Unit 1: Multi-Layer Perceptron (MLP)

Unit 1 Presentation: Multi-Layer Perceptron (MLP) Multi-Layer Perceptron Presentation Unit 1 Project: Nonlinear Rubric System Please use t...
Unit 2: Convolutional Neural Network (CNN)

Unit 2 Assignment: Convolutional Neural Network (CNN) Please use the " Basic Tutorials > Convolutional Neural Network (CNN) " o...

Basic Tutorials

Deep Learning (DL)
Multi-Layer Perceptron (MLP)
Convolutional Neural Network (CNN)
Recurrent Neural Network (RNN)

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About Me

Chin-Sung Lin: Born and raised in Taipei, Taiwan, Chin-Sung Lin earned his B.S.E.E., concentrating in Solid State Physics, from National Cheng Kung University, Taiwan. He earned his M.S.E.E.,concentrating in Image Processing and VLSI Design, from Polytechnic University, NY. He has worked in research labs and engineering R&D companies for many years. His project experience covers algorithm, hardware, software, firmware and system design in various fields such as image processing, character recognition, consumer integrated circuits, HDTV system, set-top box, stereo video projector, and media processor. He holds two U.S. Patents in the HDTV fields. In 2005, Mr. Lin entered the teaching career through the NYC Teaching Fellows program. He started teaching Technology, Physics, and various Math classes at Information Technology High School. He earned his M.S.T. from Pace University in 2008. He is passionate to share the excitement of innovative problem solving in the STEM (Science, Technology, Engineering and Mathematics) fields with students through project-based learning.

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