Are you (or is someone you know) teaching AI / ML / Deep Learning this year? My forthcoming book (freely available at https://t.co/hqRA1xUPkk) will save you a lot of time. This thread will show you why.
🎓Announcing the 1st Bath Summer School in Machine Learning
📅 5–7 August 2026 | 📌 University of Bath
Topics: ODEs/SDEs, Bayesian methods, Self-Supervised Learning, World Models
Open to PhDs, postdocs & staff at EU/UK universities
https://t.co/mRC8nNWXYY
Are you (or is someone you know) teaching AI / ML / Deep Learning this year? My forthcoming book (freely available at https://t.co/hqRA1xUPkk) will save you a lot of time. This thread will show you why.
Probability is essential for machine learning. Just added a new unit on the expectation operator which reduces a probability distribution to a single comprehensible, actionable property:
https://t.co/UcRE3QuIlP
Completely free, and includes 43 problems with answers. Enjoy!
@Elliot2718 Thanks! I think the main thing is not to worry if you get them wrong... attempting them and looking at the answer will still help you learn. Use AI to get answers for the "professor only" questions, and to generate hints where you can.
Here is part VI of my series of tutorials on ODEs and SDEs in machine learning for @RBCBorealis.
https://t.co/GzuecHr9wt
To solve SDEs we must integrate the noise term and to this end, we develop the stochastic integral. It's solution is a stochastic process with mean zero.
I was unimpressed by online education platforms, so I built my own and am migrating "Understanding Deep Learning" onto it. Features include: animations, interactive figures, problems, notebooks, and AI integration. It's early days, but feel free to take a look! Link in replies.
You can find the website at https://t.co/8zGsFiXjXd. You have to sign in (but it's free) and it's really only suitable for tablet or larger screens. Please send me feedback if it doesn't work for you!
Wow. Understanding Deep Learning has now been downloaded half a million times. Thank you so much everyone! I was overjoyed when it hit 100k so this is completely mindblowing. I'm so thrilled that people are finding it useful.
This year, I've been writing a new series of articles on ODEs and SDEs for machine learning (suitable for people with zero experience of differential equations). You can find the most recent article (on closed-form solutions for ODEs) here:
https://t.co/v6H42IUEz9
Last year I wrote seven tutorials for @RBCBorealis on infinite-width neural networks. Topics included the neural tangent network, Bayesian neural networks and Neural Network Gaussian processes. Includes working code and many novel figures.
https://t.co/FFhk9OVh7f
My friend @TylerJohnMills is looking for collaborators to work on the ARC-AGI competition. This benchmark is interesting and encourages creative approaches to AI. Tyler helped me with my book and would be a fun person to work with. Get in touch directly if you are interested.