Event Info
NOTE: Change of date of event from 24 July 2019 to 22 July 2019
Outline
- Construct and implement deep neural network (DNN) model using Plain Tensorflow with personalized red wine dataset
- Fine-tune hyperparameters (batch-size, learning rate, number of epochs, number of hidden layers, number of neurons per hidden layer, activation functions, optimizers) of DNN model in Tensorflow with personalized red wine dataset
- Implementation of regularization techniques for DNN model in Tensorflow with personalized red wine dataset
Requirements
- Basic knowledge of Python Programming
- Participants who are joining this series for the first-time should refer to this document
- Participants will need to bring their own laptops
Mode of Training
Classroom
Workshop Format
Lecture - 1 hr | Hands-on tutorial - 1.25 hr | Q & A – 0.5 hr
Trainer
Alvin Chew is currently a Microsoft Cloud Research Software Fellow and a final-year PhD candidate in School of Civil and Environmental Engineering, Nanyang Technological University.
Registration for this event has closed.
|