This lesson is being piloted (Beta version)

Instructor

  • Instructor: Tue Vu
  • Office: 119 Ford Hall, SMU
  • Email: tuev@smu.edu

Workshop Description

This is the introductory workshop on Deep Learning in Python using Keras library. Within this workshop, students will learn basic introduction to Deep Learning and basic with Keras library for Deep Neural Network. In particular, students learn how to use Keras for Classification/Regression problem, application of CNN for image classification, RNN LSTM for time series forecasting.

Pre-requisite for the course is “Introduction to Machine Learning in Python using scikit-learn”.

Course Outline

Topic

Description
Setup Preparing for the course
1. Introduction to Deep Learning What is Deep Learning
2. Deep Learning Library Framework What are Deep Learning Library Framework
3. Recap on ANN Basic of ANN
4. Introduction to Keras What are different component in Keras
5. Training Deep Learning Regression & Classiciation model with Keras Sequential How to train a Deep Learning model using Regression/Classication method with Keras
6. Keras Dense Network with MNIST/CIFAR10 Image Classification with MNIST and CIFAR10 data
7. Convolution Neural Network for image classification: CIFAR10 How to train a CNN model with Keras
8. Tensorboard What is Tensorboard and How to use?
9. Recurrent Neural Network for Stock forecasting How to train a RNN model with Keras
Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.