DDD Perth 2019 Agenda
Theatre
RR5
M6
M7
M8
M9
8:00 am - 8:45 am
Registration
8:45 am - 9:00 am
Welcome and housekeeping
9:00 am - 9:10 am
Welcome to country
9:10 am - 9:55 am
9:10 am - 9:55 am
Theatre
Jennifer Marsman
9:55 am - 10:05 am
Changeover
10:05 am - 10:25 am
Machine Learning with .NET (for Non-Data-Scientists)
RR5
Ryan Preece
10:05 am - 10:25 am
M8
Daniel Sagenschneider
What Chickens and Submarines Can Teach You About Teams
M9
Mauro Da Silva
10:25 am - 10:55 am
Morning tea
10:55 am - 11:40 am
GraphQL, gRPC or REST? Resolving the API Developer's Dilemma
Theatre
Rob Crowley
NLP for fun & business - AI at your fingertips
RR5
Diana MozoAnderson, Denis Lapchev
Coding in Interviews
M6
James Miles
DesignOps - How to get ideas out faster
M8
Kristy Sachse
How do you apply Agile on a solo project?
M9
Mo Zaatar
11:40 am - 11:50 am
Changeover
11:50 am - 12:10 pm
11:50 am - 12:10 pm
M7
Sander Huijsen
Falling For Flutter: A web developer's journey to the app store, and how you can do the same
M8
Jacob Impson
How to define a chatbot personality
M9
Marieke Lunel
12:10 pm - 12:20 pm
Changeover
12:20 pm - 1:05 pm
Design: 25 lessons from 25 years
M6
Nick Leigh, Jonathan Steingiesser
Finding a Needle in a Call Stack - Intro to Distributed Tracing
M7
Josh Michielsen
Demystifying AWS Security Services
M8
Even Zhang
Building Serverless APIs with Azure Functions and C#
M9
Will Velida
1:05 pm - 2:05 pm
Lunch
2:05 pm - 2:25 pm
2:05 pm - 2:25 pm
M7
Dave Cumming
Breaking Up With Redux: Client State Management with Apollo and GraphQL
M8
Inaie Ignacio
How to survive the stakeholder battle for features
M9
Trent Cain
2:25 pm - 2:35 pm
Changeover
2:35 pm - 3:20 pm
2:35 pm - 3:20 pm
Theatre
Ashley Aitken
Hypothesis-Driven Development: Why you need online controlled experiments to scale
M7
Tommy O'Dell
JavaScript and AI, no you're not dreaming
M8
Yaser Adel Mehraban
Kubernetes vs. Serverless - The Great Cloud Native Debate
M9
Josh Armitage
3:20 pm - 3:50 pm
Afternoon tea
3:50 pm - 4:20 pm
Prize Draw
4:20 pm - 5:05 pm
5:05 pm - 5:10 pm
Thank yous and wrap up
5:10 pm
Afterparty
Putting the fast in Fast.Ai - Machine Learning models in 15 mins
📍 M6
Recording
Watch on YouTube (opens in a new tab)Machine learning is enabling computers to learn things which are not explicitly programmable. It’s complex – involving equivalent amounts of maths and computer science. It’s daunting and often hard to figure out where to start. Fast.Ai was created with the aim of helping developers and non-technical SME’s build their own machine learning models. It provides a top-down approach which abstracts away the need for elaborate coding and complex theoretical concepts. Join me in an end to end demonstration of how to create a 95% accurate image classification model from scratch, using the Fast.Ai library. An ideal introduction to testing the waters in machine learning.
Speaker
Akanksha Malik
