In San Francisco, having wrapped filming for a series of interactive videos using TensorFlow 2.0 and Keras for Natural Language Processing, Machine Vision, and Deep Reinforcement Learning.
All of the code is available for free now in GitHub.
In San Francisco, having wrapped filming for a series of interactive videos using TensorFlow 2.0 and Keras for Natural Language Processing, Machine Vision, and Deep Reinforcement Learning.
All of the code is available for free now in GitHub.
Another day, another podcast release!
This one is with the charismatic Francesco Gadaleta on his "Data Science at Home" podcast. We talked about:
How to deal with bias in machine learning used to match jobs to candidates
Guidelines to take into account whenever you implement a deep learning model
The future of AI
My appearance on the Data Science Imposters podcast went live today. The co-hosts, Jordy and Antonio, came to untapt HQ to discuss a wildly broad range of topics that included untapt and my book, Deep Learning Illustrated. Having such warm co-hosts, as well as being able to record in-person, ensured that we created an especially fun podcast.
Had so much fun chatting with Susan Wang about deep learning on her DataBytes podcast.
Enjoyed the deeply thoughtful questions from Tobias Macey on his Python podcast, Podcast.__init__, released today. We discussed what deep learning is, how we deploy it to solve human-resources problems at untapt, and my newly-released book Deep Learning Illustrated.
I spotted Deep Learning Illustrated for the first time in-store at the Barnes & Noble location on New York’s Upper West Side.
Had a blast speaking to a packed, inquisitive house at Metis New York last week about deep learning (specifically, contrasting the TensorFlow 2.0 and PyTorch libraries) as well as signing copies of my newly-released Deep Learning Illustrated book.
Thanks to Nathan Vermeiren, Jennifer Raimone, Jane Durand, and Dun Sattler for organizing and hosting the popular event, which had a long waiting list and several hundred folks join via live stream.
Given the popularity of this topic, I’ll be sure to give this talk again soon!
It's the final chance to sign up for my comprehensive, 30-hour Deep Learning course, which kicks off on Sat Oct 19 at the NYC Data Science Academy. Use the code DLT2019 to get 10% off!
The course features the brand-new TensorFlow 2.0 library, used in conjunction with Keras and PyTorch, to cover all of the underlying Deep Learning theory and all of its modern applications. Optionally, as the course progresses, you can work with me directly to develop your own Deep Learning project from the ground up.
Here's a 30-second video of my popular course demo night last week, which also served as a book-launch / book-signing for my newly released Deep Learning Illustrated.
My newly-released book Deep Learning Illustrated became an instant #1 Bestseller this week in two Amazon Kindle categories: Neural Networks and Data Mining.
The first copies of Deep Learning Illustrated are out!
It's already topping several new-release categories on Amazon, including the Artificial Intelligence category.
I'm hoping to get Grant and Aglaé together this week for photos of the whole authorship team.
Thanks to everyone at Pearson -- especially Debra Williams Cauley -- for believing in our vision and ensuring this book was a success.
Had a blast discussing the application of data science and AI to the field of human resources on the distinguished The Recruiting Future Podcast. Many thanks to Matt Alder for having me on as a guest -- I hope to do it again soon!
My favorite talk I've ever given was a three-hour seminar on "Deep Learning for TensorFlow 2.0", which was at the Open Data Science Conference in New York in June (pictured). The venue was flawless and the audience was incredibly engaged.
I'm excited to be in San Francisco on October 30th at the massive ODSC West conference (click through to see the details within my post on the ODSC blog). I'll be offering an expanded seminar on the soon-to-be-released major update of the world's most popular deep learning library. I'll also be carrying out a book-signing of my soon-to-be-released Deep Learning Illustrated.
This week, not once — but a mind-boggling twice — blog posts featuring content from my forthcoming book Deep Learning Illustrated made the front page of Hacker News.
They’re both interactive posts by Domino Data Lab. The first, which made the front page on August 24th, is on natural language processing. The second, which is on the front page presently (August 29th), is on deep reinforcement learning.
Thrilled to be back in studio, this time filming "Deep Learning with TensorFlow, Keras, and PyTorch", which features the upcoming TensorFlow 2.0 library and will be released this autumn. All of the code is available as Jupyter notebooks in GitHub now.
My book, Deep Learning Illustrated, was released digitally today — visit informIT and use the code KROHN during checkout to get it at 35% off!
Physical copies will ship next month and can be pre-ordered via the same link.
The entirety of my first book, Deep Learning Illustrated, is now available online as a digital “rough cut”. Physical copies of the final version can be ordered and will ship soon. Click through for details, including the full Table of Contents.
For Earth Week, all of my digital content (22 hours of interactive Deep Learning tutorials) is available for 70% off. Use code EARTH until Friday :)
I'm delighted to announce that my first book is now available for pre-order! Deep Learning Illustrated is a (surprisingly) fun introduction to Artificial Intelligence that I've written with the South African scientist Grant Beyleveld and Belgian artist Aglaé Bassens.
The book is being published by Addison-Wesley and will ship in the next few months. In the meantime, a "rough cut" of the first two-thirds of it is now live in Safari Books.
Provided here are illustrations that Aglaé created of the authorship team, in the style of her illustrations throughout the book, as well as the cover art!
On November 27th, I sat on a panel discussing the present and future of artificial intelligence at Nasdaq Marketplace in New York. It was an honour to sit along side Peter Voss, originator of the now-predominant term Artificial General Intelligence, which refers to an AI that has a capacity roughly indistinguishable from that of a human.
Feeling lucky to be recognised for a genetics research prize this month by the Public Library of Science (PLOS). Data I processed years ago was unearthed for an academic paper that received broad media attention, including on the BBC and in the Daily Mail.