Accessible AI and ML for the Data Scientist
Accessible AI and ML for the Data Scientist


How can a Data Scientist readily access today's rapid advances in Artificial Intelligence and Machine Learning? Primarily using open source software, the Machine Learning Hub ( is a repository of AI and ML tools and technology, and Data Science techniques. With a simple setup on any platform, the MLHub packages provide effective demonstrations and powerful command line tools to learn from and build upon. MLHub packages are installed directly from git repositories to be run locally. We will share the latest technology and learn how to readily explore such advances in technology, covering computer vision, natural language, and machine learning.

Session Prerequisites:

Instructions for installing MLHub are available from In particular, platform options are covered in and specific install steps are covered in

Github repository:


Graham Williams is Chief Scientist with the Software Innovation Institute, Australian National University. Prior to joining the ANU, he was Director of Data Science, Cloud, and AI, with Microsoft. Graham has a Ph.D. in Machine Learning and is an AI developer, researcher, practitioner, and educator as well as an Open Source Software advocate, with over 30 years in the industry. He is the author of popular books and software, 'Data Mining with Rattle and R', and 'The Essentials of Data Science'. His contributions to Data Science in the region, including building capability across organizations in the industry, government, and academia, were recently recognized by the Pacific Asia Conference on Knowledge Discovery and Data Mining through its Special Achievement Award for extraordinary and ongoing contributions in research and service to the field.

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