One Million SuperDataScience Podcast Listens Per Quarter

We've cracked one million listens per quarter for the first time! No doubt buoyed by the mainstream A.I. fascination, but also thanks to our outstanding recent guests, our show had 1.06 million listens in Q1 2023 🍾

The chart shows episode downloads (on podcasting platforms) plus views (on YouTube) for each quarter since I took over as host of The SuperDataScience Podcast in January 2021.

Thank you for listening and providing thoughtful feedback on how we can improve the show. We have fantastic topics lined up for the coming weeks so I'm hopeful we can continue this growth trend in Q2. We're already off to a good start as the past week was — by some margin — the best week for listens in the show's history.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Live podcast recording with Hilary Mason at New York R Conference

Thanks to data science legend Hilary Mason and the engaging audience at the New York R Conference for making Friday's live-filmed episode of the SuperDataScience podcast an exhilarating and illuminating success ⚡️

Look out for Hilary's episode as #589, which will be released on July 5th.

TEDxDrexelU on Deep Learning

I'm giving my first TED-format talk at TEDxDrexelU in Philadelphia on May 21. I'll provide a visual intro to Deep Learning and to the momentous opportunity we have to shape a bewilderingly prosperous world with A.I.

There are only 100 tickets available for sale (for $15!) but my understanding is that my talk will eventually be made available on the TED YouTube channel if you can't make it in-person.

The other compelling speakers are:
• Ebony White, PhD
• Adit Gupta
• Dale Moss
• Nadia Christina Jagessar, MBA
• Dr. Nyree Dardarian
• Raja Schaar, IDSA

Event and ticket details available here.

SuperDataScience Podcast LIVE at MLconf NYC and ScaleUp:AI!

It's finally happening: the first-ever SuperDataScience episodes filmed with a live audience! On March 31 and April 7 in New York, you'll be able to react to guests and ask them questions in real-time. I'm excited 🕺

The first live, in-person episode will be filmed at MLconf NYC on March 31st. The guest will be Alexander Holden Miller, an engineering manager at Facebook A.I. Research who leads bleeding-edge work at mind-blowing intersections of deep reinforcement learning, natural language processing, and creative A.I.

A week later on April 7th, another live, in-person episode will be filmed at ScaleUp:AI. I'll be hosting a panel on open-source machine learning that features Hugging Face CEO Clem Delangue.

I hope to see you at one of these conferences, the first I'll be attending in over two years! Can't wait. There are more live SuperDataScience episodes planned for New York this year and hopefully it won't be long before we're recording episodes live around the world.

ScaleUp: AI Conference

At ScaleUp:AI in New York next month, I'll be moderating a panel on Open-Source Software that features Hugging Face CEO Clem Delangue. Other speakers include Andrew Ng, Allie K. Miller, and William Falcon.

Thanks to the folks at Insight Partners for putting together this high-octane, two-day event, in which you'll hear from the foremost thought leaders and investors on how to unlock your firm's A.I. growth potential.

So excited to be conferencing in-person again and I hope to be able to meet you there! There is a virtual option as well if you can't make it to New York. Whether in-person or virtual, you can use my code "JKAI35" to get 35% off 😀

Conference details/registration here.

Full speaker list here.

Courses in Data Science and Machine Learning

This week's guest is super fun Sadie St. Lawrence, an exceptionally popular data science instructor with over 300k students all-time. She fills us in on her exciting new ML Certificate and the global impact of her Women In Data org.

Sadie:
• Teaches data science at the University of California, Davis
• Her Coursera course is one of the all-time most popular
• Is Founder and CEO of Women in Data, a community of 20k across 15 countries
• Holds a Master's in Analytics from Villanova University

In this episode, she digs into:
• The content of her existing iconic data science course
• The curriculum of her epic forthcoming Machine Learning Certificate
• The mission, impact, and vision of the Women in Data organization
• Her path into data science from music performance
• Non-fungible tokens (NFTs) and the future of technology

Thanks to Harpreet Sahota for introducing me to Sadie! I absolutely loved filming this episode.

Listen or watch here.

"Math for Machine Learning" course on Udemy complete!

After a year of filming and editing, my "Math for Machine Learning" course on Udemy is complete! To celebrate, we put together this epic video that overviews the 15-hour curriculum in under two minutes.

Over 83,000 students have registered for the course, which provides an introduction to all of the essential Linear Algebra and Calculus that one needs to be an expert Machine Learning practitioner. It's full of hundreds of hands-on code demos in the key Python tensor libraries — NumPy, TensorFlow, and PyTorch — to make learning fun and intuitive.

You can check out the course here.

Translations of Deep Learning Illustrated – Now available in Traditional Chinese

My book, Deep Learning Illustrated, recently became available in Traditional Chinese alongside the existing Russian, German, and Korean translations. The new edition instantly became a #1-bestseller in Taiwan.

Thanks to Neville Huang for diligently translating to Traditional Chinese from the original English. Neville also tipped me off to the #1-bestseller status — I've put the screenshot he shared with me on LinkedIn.

O'Reilly + JK October & November ML Foundations LIVE Classes open for registration

We're halfway through my live 14-class "ML Foundations" curriculum, which I'm offering via O'Reilly Media. The first Probability class is on Wednesday with five of the seven remaining classes open for registration now:

• Oct 6 — Intro to Probability
• Oct 13 — Probability II and Information Theory
• Oct 27 — Intro to Statistics
• Nov 3 — Statistics II: Regression and Bayesian
• Nov 17 — Intro to Data Structures and Algorithms

The final two classes will be in December and are on Computer Science topics: Hashing, Trees, Graphs, and Optimization. Registration for them should open soon.

All of the training dates and registration links are provided at jonkrohn.com/talks.

A detailed curriculum and all of the code for my ML Foundations series is available open-source in GitHub here.

O'Reilly + JK October ML Foundations LIVE Classes open for registration

The Linear Algebra classes of my "ML Foundations" curriculum, offered via the O'Reilly Media platform, are in the rear-view mirror. Two Calculus classes are coming up soon and the Probability classes just opened for registration:

• Sep 15 — Calculus III: Partial Derivatives
• Sep 22 — Calculus IV: Gradients and Integrals
• Oct 6 — Intro to Probability
• Oct 13 — Probability II and Information Theory
• Oct 27 — Intro to Statistics

Overall, four subject areas are covered:
• Linear Algebra (3/3 classes DONE)
• Calculus (2/4 classes DONE)
• Probability and Statistics (4 classes)
• Computer Science (3 classes)

Hope to see you in class! Sign up opens about two months prior to each class. All of the training dates and registration links are provided at jonkrohn.com/talks

A detailed curriculum and all of the code for my ML Foundations series is available open-source in GitHub here.

A4N Episode 5: We're on Pause for Now!

In this episode of A4N, I have a special announcement! While the A4N podcast will be going on indefinite hiatus, it is because I am now hosting the SuperDataScience Podcast. If you enjoyed A4N then you're sure to enjoy the SuperDataScience podcast, which publishes twice every week on Tuesdays and Fridays!

You can check it out here.

TensorFlow vs PyTorch @ DataScienceGo Virtual

The DataScienceGO Virtual conference is coming up next Saturday and it is FREE! I'm giving a talk on TensorFlow vs PyTorch with lots of time for audience questions.

Data Community Content Creator Awards

I am surprised and utterly delighted to be recognized yesterday with the Data Community Content Creator Award for the "Machine Learning and AI" YouTube category. 🥳

From my perspective, my YouTube channel is still in its early days so while I did not anticipate formal recognition like this perhaps ever, I *certainly* did not so soon after launching the channel. This is a massive, galvanizing signal that I should continue pressing on with this nascent video-creation effort — I absolutely will!

First off, thank you to everyone who voted. This category was apparently one of the tightest races in this "Peoples' Choice"-style awards show, so truly your individual vote may have tipped the award in my favor.

Many thanks are due to Sangbin Lee and Maria Lee, who have edited, produced, branded, and marketed every single video on my channel since day one. My freely-available YouTube content would not exist without them. Thanks as well to Guillaume Rousseau, who recently joined us and dramatically accelerated how quickly we can publish perfectly-edited videos.

Finally, thanks to Harpreet Sahota and Kate Strachnyi who conceived of the DCCCA show and delivered it with the flair, fun, and precision that we'd expect from them!

The entire ceremony is on YouTube here. And a short recap post is here.