16-19 October 2018
Asia/Taipei timezone
Online early bird registration is now open

Tutorials

Tutorial Session I: (booked by NI)

(09:00 ~ 10:30)

 

Tutorial Session II: Building Predictive Models for Sensor Data Analytics

(10:50 ~ 12:20)

Speaker: Jeffrey Liu (TeraSoft Inc.)

Machine learning and Deep Learning are quickly becoming powerful tools for solving complex modeling problems across a broad range of industries. The benefits of machine learning are being realized in applications everywhere, including predictive maintenance, health monitoring, financial portfolio forecasting, and advanced driver assistance.  However, developing predictive models for signals is not a trivial task. In addition, there is an increasing need for developing smart sensor signal processing algorithms which can be either deployed on edge nodes or on the cloud. 

In this session we will explore how you can use MATLAB for developing predictive models for real world sensor analytics using machine learning and deep learning workflows.

 

Tutorial Session III: Dive into Python

(13:30 ~ 15:00)

Speaker: Chi-Hung Weng

Speaker will showcase some possible applications written in Python, ranging from web crawling, data cleaning, data visualization, to Machine Learning and Deep Learning. We then make an excursion to Deep Learning, where the following questions are to be answered: what is Deep Learning? what’s the theory behind it? What’s the difference between Deep Learning frameworks such as TensorFlow, Keras, MXNet and Pytorch?

 

Tutorial Session IV: Deep Learning

(15:20 ~ 17:00)

Speaker: Chi-Hung Weng

Speaker will demonstrate & explain several deep learning applications in Computer Vision, including: image classification, object detection and semantic segmentation. Sample codes and datasets will be provided during the session.

 

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