Getting Value From A.I.

My keynote on "Getting Value from A.I." — which I delivered at Hg Capital's "Digital Forum" in London — is now live on YouTube!

With a focus on B2B SaaS applications, over 45 minutes I covered:
1. What Deep Learning A.I. is and How it Works
2. Tasks that are Replaceable with A.I. vs Tasks that can be Augmented
3. How to Effectively Implement A.I. Research into Production

The audience engagement was terrific and the on-stage Q&A carried on afterward for an energizing 20 additional minutes. All of this is captured in the slickly-edited video production.

Deep Reinforcement Learning — with Wah Loon Keng

For an intro to Deep Reinforcement Learning or to hear about the latest research and applications in the field (which is responsible for the most cutting-edge "A.I."), today's episode with Wah Loon Keng is for you.

Keng:
• Co-authored the exceptional book "Foundations of Deep Reinforcement Learning" alongside Laura Graesser.
• Co-created SLM-Lab, an open-source deep reinforcement learning framework written with the Python PyTorch library.
• Is a Senior A.I. Engineer at AppLovin, a marketing solutions provider.

In this episode, Keng details:
• What reinforcement learning is.
• A timeline of major breakthroughs in the history of Reinforcement Learning, including when and how Deep RL evolved.
• Modern industrial applications of Deep RL across robotics, logistics, and climate change.
• Limitations of Deep RL and how future research may overcome these limitations.
• The industrial robotics and A.I. applications Deep RL could play a leading role in in the coming decades.
• What it means to be an A.I. engineer and the software tools he uses daily in that role.

The SuperDataScience show's available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Binary Classification

Last week, I kicked off a series of YouTube videos on Integral Calculus. To provide a real-world Machine Learning application to apply integral calculus to, today's video introduces what Binary Classification problems are.

We publish a new video from my "Calculus for Machine Learning" course to YouTube every Wednesday. Playlist is here.

More detail about my broader "ML Foundations" curriculum and all of the associated open-source code is available in GitHub here.

Deep Learning Battle: Pytorch vs. Tensorflow

When I teach Deep Learning, the question I get most often is: "Should I be using TensorFlow or PyTorch?" In this recent talk at the DataScienceGO conference, I provide my most thorough and polished response yet.

Thanks to Harpreet Sahota for hosting the session masterfully and leading the audience Q&A at the end.

Intro to Deep Reinforcement Learning at Columbia University

My goodness did I ever miss lecturing in-person! Was finally back in front of a live classroom on Friday, providing an intro to Deep Reinforcement Learning to engineering graduates at Columbia University in the City of New York.

Thank you Chong and Sam for having me. It's always a delight to lecture to your brilliant ELEN E6885 students, especially now that the pandemic is subsiding and I can interact with them meaningfully again.

You can see the slides from here as well as the associated GitHub repository here.