Tutorial: Programming Deep Learning in TensorFlow with Smart City Applications
Description: TensorFlow is a Python based framework that provides facility to use deep
learning algorithms for forecasting different practical life scenarios. This could be applied
to both, classification and regression problems. In this workshop, we will mainly focus on
its application on forecasting traffic behavior in cities and on expressways. With the help
of some examples, we will explain how it could be used to train the deep models and how
the trained models could be used to predict the behavior. There will be some hand-on
activities as well so that you could build and run deep models using TensorFlow.
Laptops are needed: attendees will practice installation and programming in TensorFlow
on their laptops.
Level: Basic/Intermediate
Prerequisites: Experience on programming (Python), basic knowledge of machine
learning.
Audience: Students, academic researchers, data scientists, or data analysts having prior
programming experience (preferably Python) and basic knowledge of machine learning.
Contents:
- Introduction to TensorFlow
- Basic operations in TensorFlow
- Linear Regression
- Optimizers and Loss Functions
- Recurrent Neural Networks