Practical Geometric Deep Learning in Python Pantelis Elinas YOW! 2019

This presentation was recorded at YOW! 2019. #GOTOcon #YOW Pantelis Elinas - Principal AI/ML Engineer & Team Leader at CSIRO's DATA61 RESOURCES @ ABSTRACT #GeometricDeepLearning (#GDL) is a fast developing machine learning specialisation that uses the network structure underlying the data to improve learning outcomes. GDL has been successfully applied to problems in various domains with network-structured data, such as social science, medicine, media, finance, etc. Inspired by the success of neural networks in domains such as computer vision and natural language processing, the core component driving GDL is the #GraphConvolutionOperator. This operator is used as the building block for deep learning models applied to networks. This approach takes advantage of many algorithmic and computational developments from modern neural network research and practice – such as composability, optimisation, and end-to-end training – to improve predictive performance. However, there is a lack of tools for geometric #DeepLearning targeting data scientists and #MachineLearning practitioners. In response, #CSIRO’s #Data61 has developed #StellarGraph, an open source #Python library. StellarGraph implements a number of state-of-the-art methods for GDL with a clean and consistent API. Furthermore, StellarGraph is designed to make the application of GDL algorithms to network-structured data easy to integrate with existing machine learning workflows. In this talk, we will start with an overview of GDL and its real-world applications. Then we will introduce StellarGraph with a focus on its design philosophy, API and analytics workflow. Finally, we will demonstrate StellarGraph’s flexibility and ease-of-use for developing solutions targeting important applications such as product recommendation and social network moderation. Lastly, we will touch on the challenges of designing and implementing a library for a fast evolving machine learning field. [...] RECOMMENDED BOOKS Stefan Helzle • Low-Code Application Development with Appian • Phil Winder • Reinforcement Learning • Kelleher & Tierney • Data Science (The MIT Press Essential Knowledge series) • Lakshmanan, Robinson & Munn • Machine Learning Design Patterns • #PantelisElinas #ArtificialIntelligence #ChatGPT #OCR #ReinforcementLearning #SoftwareEngineering #Programming #YOWcon Looking for a unique learning experience? Attend the next GOTO conference near you! Get your ticket at Sign up for updates and specials at SUBSCRIBE TO OUR CHANNEL - new videos posted almost daily.