Practical Deep Learning for Complete Beginners
Organizers: Dr. Abhijeet Ravankar, Dr. Ankit Ravankar, Dr. Takanori Emaru
Lab of Robotics and Dynamics, Hokkaido University, Japan
Time: 9:00-12:00, December 13, 2017
I hear and I forget. I see and I remember. I do and I understand. - Confucius
This hands-on tutorial aims at making participants comfortable with major deep learning concepts. The tutorial covers a broad range of topics in deep learning. Participants will learn the theory, and run the code on their laptop. Although, it does not dive deep into the mathematical models behind deep learning, the attendees will be given appropriate pointers to resources to further explore the topics.
Deep learning is one of the fastest growing areas of machine learning and a hot topic in both academia and industry. Deep learning has successfully been used in robotics, controls, systems, computer vision, and many other fields. You are likely to encounter a research paper in your field which uses deep learning as a tool. This tutorial is aimed at complete beginners in Machine/Deep learning to provide a thorough and intuitive understanding of major topics in deep learning like: Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs), including Restricted Boltzmann Machines (RBMs), and AutoEncoders. Additionally, participants will be able to run the code on their own laptops to reinforce their understanding of the concepts.