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TensorFlow and Deep Learning Malaysia Meetup

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TensorFlow and Deep Learning Malaysia Meetup

14 March 2018 7:00pm - 9:00pm
MaGIC (Malaysian Global Innovation & Creativity Centre) View map
Admission is FREE
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Join two hours session with 2 speakers topics related to machine learning and deep learning.

Learn and implement how real-life data machine learning/deep learning can be applied to solving commercial problems.

Agenda of the event :

Time Activity
6.00 PM Registration
7.00 PM Opening Remarks
7.15 PM Welcoming address
7.20 PM Session 1 “Build your first Android Image Classifier with Tensorflow”
8.00 PM Break & Networking Session
8.10 PM Session 2 “Convolutional Neural Network Architectures”
8.50 PM Break & Networking Session
9.00 PM End

Event Description:

Build your first Android Image Classifier with Tensorflow
TensorFlow is an open source software library for machine learning, developed by Google and currently used in many of their projects. In this talk, participants will learn an easy, fast, and fun way to get started with TensorFlow by building an Android image classifier: an offline and simplified alternative to Google’s Cloud Vision API where Android device can detect and recognize objects from an image.
Convolutional Neural Network Architectures
Computer Vision has been applied to many applications, such as search, image understanding, mapping, medicine, drones, and self-driving cars. The Core to many of these applications is visual recognition tasks such as image classification, localization, and detection. Recent advancement in neural network (aka “deep learning”) has greatly increased the performance of the state-of-the-art visual recognition systems which makes them more practical and ready-to-use in industry.
This talk is an introduction to convolutional neural network and its applications to computer vision, particularly image classification. Moreover, the talk will cover the basic building blocks of deep convolutional neural networks such as Max-Pooling and Dropout. And then briefly explain the major architecture such as DenseNet, Dual-Path and Squeeze and Excitation networks. The talk will end with a simple demonstration of applying deep learning using Keras library.

Who should join us?

  • Startups
  • Machine learning
  • Deep Learning
  • Developers
  • Community
  • Innovators
  • Professionals
  • Business
  • Students

Our Speakers

Christine Tee

Christine is a Masters in Computer Science (Artificial Intelligence) graduate from UM. She is also one of the organizing members of GDG Kuala Lumpur. While she currently works as a freelance programmer, she also demonstrated her passion for technology as a technology writer for Droid-Now, PRWIRE Asia and Penman Publishing.

Mundher Al-Shabi

Mundher is a scholar, scientist, and engineer in artificial intelligence (AI). Currently, he is doing his PhD in deep learning at Monash University. He has published several research papers in deep learning and machine learning. Besides that, he is an AI consultant at geekhub where he works with other engineers side-by-side to solve technical problems.
His expertise lies in machine/deep learning and computer vision. He is interested in applying machine learning to different domains to make human life much better, safer and more effective.
He spends his free time to democratize AI by spreading the knowledge and help people across social media to solve AI technical problems.