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YOW! Data is a technical conference for data professionals which provides the opportunity to share challenges, best practices, experience, techniques and tools.

The conference brings together leading industry practitioners and applied researchers working on data-driven technology and applications, providing in-depth coverage of current and emerging technologies in the areas of Big Data, Analytics and Machine Learning. Network, meet the experts and hone your skills all in one event.

Keynotes and Invited Speakers

Juliet Hougland

Data Vagabond

Bagged & Boosted

Juliet Hougland

How to Experiment Quickly

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Simon Kaplan

CEO

[ui!] the urban institute

Simon Kaplan

Lessons from Building a Data Platform for Smart Cities

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Speakers

Agustinus Nalwan

AI & Machine Learning Technical Development Manager

Carsales.com

Agustinus Nalwan

The Magic of Unsupervised Learning: Teaching an AI to Understand Our World

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Ananth Gundabattula

Sr. Architect

Commonwealth Bank of Australia

Ananth Gundabattula

Auto feature engineering - Rapid feature harvesting using DFS and data engineering techniques

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Anthony I Joseph

Chief Technology Officer

My House Geek Pty Ltd

Anthony I Joseph

Techniques Used to Analyse the Affordability, Commutability and Demographics of Real Estate in School Catchment Areas

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Antoine Desmet

Analytics Manager

Komatsu

Antoine Desmet

From Zero to Tensorflow: Building an Analytics Dept.

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Brad Urani

Staff Engineer

Procore

Brad Urani

My 5 Biggest Database Blunders

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Brendan Hosking

Solutions Engineer

CSIRO

Brendan Hosking

Custom Continuous Deployment to Uncover the Secrets in the Genome

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Dana Ma

Sr. Software Engineer

Zendesk

Dana Ma

Building Rome Every Day - Scaling ML Model Building Infrastructure

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Daniel Deng

Sr. Data Engineer

AirTasker

Daniel Deng

Look at GDPR from a Data Engineering Perspective

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Diana Mozo-Anderson

Marketing Science Lead

VGW

Diana Mozo-Anderson

Predictive Modelling for Online Advertising

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Enrique Bustamante

Loyalty Data Analyst

EB Games Australia

Enrique Bustamante

From Sparse Data-sets to Graphs: When Explicit Relationships Bridge the Gaps

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Gareth Seneque

Machine Learning Engineer

Australian Broadcasting Corporation

Gareth Seneque

Search at Scale: Using Machine Learning to Automate Content Metadata

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Hercules Konstantopoulos

Sr. Data Scientist

Atlassian

Hercules Konstantopoulos

Is Agile Data Science a thing now?

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Huon Wilson

Sr. Software Engineer

CSIRO's Data61

Huon Wilson

Entity Resolution at Scale

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Itzik Feldman

Product Manager for Data Engineering and Analytics

Atlassian

Itzik Feldman

Scaling Analytics as your Company Grows

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J. Rosenbaum

Artist

J. Rosenbaum

J. Rosenbaum

Artificial Intelligence and Augmented Reality: A Match Made in Heaven

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Jessica Flanagan

Chief Data Architect

Deckard Technologies

Jessica Flanagan

Working with Large Numbers of Non-Trivial ETL Pipelines

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Justin Hamman

Sr. Developer

REA Group

Justin Hamman

Building a Scalable Data Science Pipeline at REA

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Jack Low

Sr. Developer

REA Group

Jack Low

Building a Scalable Data Science Pipeline at REA

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Kale Temple

Co-founder & Practice Director

University Of Sydney

Kale Temple

Modern Time-Series Methods

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Kevin Jung

Software Engineer

CSIRO's Data61

Kevin Jung

Bitcoin Ransomware Detection with Scalable Graph Machine Learning

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Larene Le Gassick

Inclusion Engineer

larene.dev

Larene Le Gassick

Data Driven Diversity

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Lex Toumbourou

Sr. Consultant

ThoughtWorks

Lex Toumbourou

Emerging Best Practices for Machine Learning Engineering

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Linda McIver

Executive Director

Australian Data Science Education Instute

Linda McIver

The Sceptical Data Scientist

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Mat Kelcey

Machine Learning Principal

ThoughtWorks

Mat Kelcey

Practical Learning To Learn

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Mel Flanagan

Content & Service Designer

Nook Studios

Mel Flanagan

Transparent Government: The Stories we can Tell with Data

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Noon van der Silk

Director

Braneshop

Noon van der Silk

How Much Data do you _really_ need for Deep Learning?

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Pantelis Elinas

Sr. Research Engineer

Data61/CSIRO

Pantelis Elinas

Practical Geometric Deep Learning in Python

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Paola Oliva-Altamirano

Data Scientist

Our Community

Paola Oliva-Altamirano

CLASSIEfier: Using Machine Learning to Paint a Picture of Social Sector Trends

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Paris Buttfield-Addison

Founder

Secret Lab

Paris Buttfield-Addison

Game Engines and Machine Learning: Training a Self-Driving Car Without a Car?

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Mars Geldard

Researcher

University of Tasmania

Mars Geldard

Game Engines and Machine Learning: Training a Self-Driving Car Without a Car?

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Reza Yousefzadeh

Principal Data Engineer

SEEK

Reza Yousefzadeh

Bringing Continuous Delivery to Big Data Applications

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Robin Champseix

Data Scientist

OCTO Technology

Robin Champseix

New Technologies to the Rescue of Epileptics

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Roger Qiu

Principal Machine Learning Engineer Consultant

Matrix AI

Roger Qiu

Image Classification in a Noisy Fraudulent World - A Journey of Computational and Statistical Performance

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Simon Aubury

Data Engineer Architect

IAG

Simon Aubury

Which Plane Woke Snowy the Cat?

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Simon Belak

Mad Scientist

Metabase

Simon Belak

Sketch algorithms

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Simon T. O'Callaghan

Sr. Research Engineer

Data61 & Gradient Institute

Simon T. O'Callaghan

Engineering an Ethical AI System

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Alistair Reid

Sr. Research Engineer

Gradient Institute

Alistair Reid

Engineering an Ethical AI System

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Finn Lattimore

Research Scientist

Gradient Institute

Finn Lattimore

Engineering an Ethical AI System

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Suneeta Mall

Sr. Data Scientist

Nearmap

Suneeta Mall

The Three-Rs of Data-Science - Repeatability, Reproducibility, and Replicability

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Trish Khoo

Director

Transparo

Trish Khoo

Taming the Beast: Automated Testing for Complex Data Pipelines

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Xuanyi Chew

Chief Data Scientist

Ordermentum

Xuanyi Chew

Making The Black Box Transparent: Lessons in Opacity

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Yanir Seroussi

Distinguished Data Scientist

Automattic

Yanir Seroussi

Bootstrapping the Right Way

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