Advanced machine learning for science

Machine Learning Workshop Description:

CSIRO is holding a 2-days multidisciplinary workshop on Machine Learning that will integrate the most fundamental theory, cutting-edge technologies and its real-world implementations in this field.

The Machine Learning workshop aims to:

1. Bring together researchers from different fields to discuss Machine Learning related science and application challenges
2. Exchange knowledge and opinion between researchers working in Machine Learning algorithms, infrastructures, and its applied research background
3. Initiate and enhance collaborative partnerships between CSIRO and other experts in the field of Machine Learning

Amongst the invited trainers and speakers are scientific and technical leaders in this field from CSIRO.

Webpages:

C3DIS: https://wp.csiro.au/c3dis/

Machine Learning Workshop: http://wp.csiro.au/c3dis/workshops/advanced-machine-learning-for-science/

Key Points to Address:

1. Basic Introduction and Overview to Machine Learning (Hands-on/Seminar)
2. Studies Cases on Different Scientific Topics (Seminar/Presentation)
3. Hands on Lab Tutorial (Advanced Techniques of Machine Learning)
   1. Spark + Machine Learning (Big Data)
   2. Tensorflow + Deep Learning (NVIDIA Digits, Keras and Tensorflow)
4. Panel discussion & QA
5. One-on-one discussion (10mins each audience) with ML experts about “How to better utilize ML in your project”

 

Agenda

Time	Session
09:00 am – 10:30 am	Hands-on Lab for Deep Learning Christopher Watkins ·         NVIDIA Digits ·         Keras
10:30 am – 11:00 am	Morning Tea and Networking
11:00 am – 12:00 am	Hands-on Lab for Deep Learning Christopher Watkins ·         Tensorflow
12:00 pm – 13:30 pm	Lunch and Networking
13:30 pm – 15:00 pm	Presentation 1.    Deep learning based fish detection and classification for the monitoring of fisheries operations (Deep Learning) Dadong Wang 2.    Human behaviour analytics – of users, by users, and for users (Recommendation System) Shlomo Berkovsky 3.    Applications of machine learning models in Agriculture and Mining Andrew Hellicar, Ashfaqur Rahman 4.    Self-organising Map (SOM) on high-dimensional data representation (Dimension Reduce) Baichuan Sun
15:00 pm – 15:30 pm	Afternoon tea and networking
15:30 pm – 16:15 pm	Panel Discussion with all speakers from the day
16:15 pm – 17:00 pm	One-on-One Q&A

 

What you need to bring for Hands-on Labs:

All audience must bring their own laptop:

• No tablets
• Requires dual-core processor with 4GB of RAM and Wi-Fi enabled
• Power cable

Date and time

Thursday 20th July, 2017.

Location

Room: Clarendon A, level 5.
Melbourne Convention and Exhibition Centre
1 Convention Place, Melbourne, Victoria

Contact information

Baichuan Sun: Baichuan.Sun@data61.csiro.au

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