Workshops


12, 19 APR 2017

Deep Learning 2-Day Workshop

Deep Learning Workshop

Day 1 - WED 12 APR 2017 10AM - 5PM
Day 2 - WED 19 APR 2017 10AM - 5PM
Silverpond Office
Level 2, 382 Little Collins Street, Melbourne

Venture into deep learning with this 2-day workshop that will take you from the mathematical and theoretical foundations to building models and neural networks in TensorFlow. You will apply as you learn, working on exercises throughout the workshop. The second day will see attendees team up and build a model (or two!) together in TensorFlow. The group will meet again in a few weeks for a “show and tell”, where attendees can share their deep learning developments.

This hands-on workshop is ideal for both data science and programming professionals, who are interested in learning the basics of deep learning and embarking on their first project.

We’ll cover:

  • Machine learning fundamentals
  • Building models in TFLearn/TensorFlow (with Python)
  • Representation Learning/Word Embeddings
  • Convolutions/Pooling
  • Solving a simple neural network by hand to consolidate knowledge
  • Hands-on exercises in a collaborative environment
  • Using TensorFlow as a general computation engine

Breakdown:

Here’s what the days will look like:

  • Day 1 - Fundamentals, Convolutions, Embeddings, Exercises.

The first day will see us learn as a group, working through exercises and building up a solid base of knowledge around deep learning.

We will cover key concepts in the field and introduce them with examples.

  • Day 2 - Group projects.

The second day will see us consolidate our knowledge by working in small groups on complete projects. A few project options will be provided across image processing, natural language processing (NLP), and generative models.

This day will build real-world experience in deep learning model development.

Outcomes include:

  • An intuitive understanding of the components of machine learning systems
  • Experience building neural networks in TensorFlow and TFLearn
  • Clear understanding of convolutions and representation learning
  • Experimenting with a model that learns representations of words
  • Practical real-world model development in TensorFlow

You have:

  • A laptop that can connect to the internet
  • Basic Python skills,
  • A willingness to learn mathematics

Note: This workshop will not require any setup - each attendee will be working in an pre-setup environment.

Workshop reviews

“I found this a fun introduction to deep learning fundamentals, tensorflow toolkit and how it can be applied to real world situations. Sometimes you just need a bit of a bootstrap to get your going with an emerging technology, and this course does just that.” – Maree

“The workshop was great and I would definitely recommend to everyone who wants to learn deep learning with real world examples. Basic concepts are introduced during the workshop and programming exercises are given to aid the learning.” – Selva

As the top “deep learningers” in the town, the organisers have profound knowledge and experience. They are also active in sharing their knowledge and getting more people interested. Their lecture notes are fascinating and can engage audiences of all levels. If you ever got buzzed by “deep learning”, here’s where you should go. – Fei

Your Instructors

Noon van der Silk
Noon is a long-time programmer who recently obtained a Masters in Pure Mathematics from The University of Melbourne. He enjoys functional programming and thinking of fun and interesting applications of deep learning. He has previously been mistaken for a paper-reading robot.


Lyndon Maydwell
Lyndon can code his way out of a wet paper bag, and has done so in the past. He enjoys thinking of new and interesting ways to understand and work with ideas in deep learning and excels at expressing complicated concepts concisely (and occasionally writing those concepts down in esoteric programming languages).


Adel Foda
Adel is a data scientist and computational linguist at heart. His deep learning repertoire spans images, video, audio, and text. Adel has an interest in pedagogy and is a regular presenter at meetups and industry events on topics of applied science.


Martin Ingram
Martin studied Physics at the University of Cambridge followed by an MSc in Computing Science from Imperial College London. He specialises in deep learning for computer vision and sports analytics. In his spare time, Martin enjoys predicting tennis matches - through mathematical modelling of course.



Day 1 - WED 12 APR 2017 10AM - 5PM
Day 2 - WED 19 APR 2017 10AM - 5PM
Silverpond Office
Level 2, 382 Little Collins Street, Melbourne

Questions? Contact us!


Register your interest in future courses like this


3 MAY 2017

Deep Learning Workshop Show and Tell

Deep Learning Show and Tell

WED 3 MAY 2017 5.30PM - 8PM
Silverpond Office
Level 2, 382 Little Collins Street, Melbourne

Learning is best done through doing. If you’ve attended one of our deep learning workshops, we invite you to join us for a little round of Show and Tell.

This is a casual gathering of deep learning learners; to share any projects you may be working on and bounce ideas off one another. Just as learning by doing is best, improving by sharing is even better.

We also welcome talks from attendees on areas of deep learning that they find interesting, papers or articles that they’ve found useful, or just ideas that they want to explore. Talk lengths can vary from 5 minutes up to 25 minutes.

Agenda

5.30pm - Arrive
5.45pm - Welcome
6pm - Talks by workshop attendees & open discussion
8pm - Wrap up



Deep Learning Course

Find more details on the upcoming Silverpond Deep Learning Course here.


Level 2
382 Little Collins Street
Melbourne VIC, 3000

Enter from McKillop Street

Contact us

(03) 9008 5922

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