Running Simulations and generating Synthetic Data in order to create more-powerful Machine Learning models is this week's topic. Bewilderingly interesting two-time book author Mars Buttfield-Addison is our guest.
Mars:
• Is co-author of two O'Reilly Media books, "Practical Simulations for Machine Learning" and "Practical Artificial Intelligence with Swift".
• Is pursuing a PhD in computer engineering from the University of Tasmania, focused on writing high-performance software to track space objects.
• Teaches courses on A.I. and data science at the University of Tasmania.
• Is a regular speaker at top tech conferences around the world.
• Holds a bachelor’s degree in software development and data modeling.
Today’s episode should be equally fascinating to technical and non-technical folks alike.
In this episode, Mars details:
• What simulations and synthetic data are, and why they can be invaluable for real-life applications.
• How simulated bots can solve any problem by representing the problem as a 3D visualization.
• Why the mobile operating system language Swift is interesting for A.I.
• How much junk there is in space and why it’s critical we track it.
• What it’s like creating video games in a “secret” Tasmanian games lab.
• Whether programming or statistical skills are more important in data science.
• Why you might want to do a data science internship in industry if you’re thinking of having a career in academia.
Thanks to Suzanne Huston for introducing me to Mars :)
The SuperDataScience show's available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
