Deep Learning Short Course

Seminar Room #6, Aug. 18

– Overview 

Artificial Intelligence (especially Machine Learning) is a technology that is attracting much attention now. It is sometimes referred to as a technology that can change the world. The need for Artificial Intelligence knowledge is increasing, in this rapidly changing world.

This course is aimed at all student from elementary school to undergraduate who are interested in Artificial Intelligence including Deep Learning and wish to learn more about this rapidly.

– Schedule & Brief introduction (will be update)

Deep Learning Short course is consist of 4 lectures what as follows.

  1. What is Artificial Intelligence?

09:20-10:50 (90’)

– A brief introduction to AI, and an introduction to Neural Network.

– Solve XOR gate using Neural Network structure

– Visualize single Neural Network for XOR gate using R

  1. Deep Neural Network to MNIST

11:10-12:40 (90’) 

– An introduction to Deep Learning.

– Implement the Deep Neural Network for MNIST, using TensorFlow.

– A brief introduction to AWS and Python for working with TensorFlow.

  1. Convolution Neural Network

14:00-15:30 (90’) 

– An Introduction to Convolution Neural Network(CNN)

– How does CNN perform well in classifying images?

– Implement the CNN for MNIST, using TensorFlow.

– AlexNet

  1. Advanced Technique : How to Improve your model

15:50-17:20 (90’)

– Few Technique about Initialize, optimizer, and so on.

– Implement your model to classify MNIST with 99% accuracy.

* It is strongly recommended to take all the lectures sequentially.

– Lecturer and Assistant

– Lecturer

Jinho Kim, Departments of Social Network Science

Ph.D Candidate at Kyung Hee University

Lecture Experience

– Tangible Artificial Intelligence, Makewith, 4th Industry School 4.0, 2017 (teaching assistant)

– An Introduction to Deep Learning, SNS open Seminar #2, 2017

– An Introduction to Deep Learning, SNS open Seminar #1, 2016

– C, Python and Deep Learning, Kyung Hee univ. Big Leader 4th, 2016.

– Assistants

YuJeong Hwangbo, Department of Social Network Science

Doctor’s Course at Kyung Hee University

Junwoo Kwon, Department of Social Network Science

Master’s Course at Kyung Hee University

– Applications

The Application process for this course will be update.