XCME011 - Introduction to Deep Learning
This workshop will present modern neural network based techniques that are used in supervised learning. We will cover the basic fundamentals required to understand how neural networks work and on applications of neural networks to problems in computer vision and natural language processing.
Prerequisites: basic concepts from linear algebra, such as vectors and matrices, calculus, such as differentiation, and probability theory, such as random variables, probability distributions and expectations. Familiarity with the python programming language and Tensorflow also required.
A good introduction to the required background material can be found here.
1.1 Introduction to Neural Networks
1.2 Fundamentals of Deep Learning
1.3 Fully-Connected networks
2. Computer vision and Natural Language Processing (NLP)
3.1 Tensorflow walkthrough of image classification with convolutional networks
3.2 Tensorflow walkthrough of next character prediction with recurrent networks
The ICME offers summer workshops to students, partners, and the wider community (first come first served, in that order). These day-long workshop happen from August 14-18, 2017, from 9:00am to 4:45 pm. To view other workshop descriptions, or to get general information about the ICME Summer Workshop Series, click here.
ICME Summer Workshops are open to participants 18 years and older. If you are under the age of 18 and would like to participate, please contact the program administrator.
Questions? Please contact ICME