Machine-Learning on Aneesh Sathe

AI: Explainable Enough

Wed, 23 Jul 2025 05:50:31 +0000

They look really juicy, she said. I was sitting in a small room with a faint chemical smell, doing one my first customer interviews. There is a sweet spot between going too deep and asserting a position. Good AI has to be just explainable enough to satisfy the user without overwhelming them with information. Luckily, I wasn’t new to the problem.

Coming from a microscopy and bio background with a strong inclination towards image analysis I had picked up deep learning as a way to be lazy in lab. Why bother figuring out features of interest when you can have a computer do it for you, was my angle. The issue was that in 2015 no biologist would accept any kind of deep learning analysis and definitely not if you couldn’t explain the details.

My Road to Bayesian Stats

Tue, 22 Jul 2025 06:32:55 +0000

By 2015, I had heard of Bayesian Stats but didn’t bother to go deeper into it. After all, significance stars, and p-values worked fine. I started to explore Bayesian Statistics when considering small sample sizes in biological experiments. How much can you say when you are comparing means of 6 or even 60 observations? This is the nature work at the edge of knowledge. Not knowing what to expect is normal. Multiple possible routes to a seen a result is normal. Not knowing how to pick the route to the observed result is also normal. Yet, our statistics fails to capture this reality and the associated uncertainties. There must be a way I thought.

Jan 4, 2025

Sun, 05 Jan 2025 00:30:49 +0000

Bayesian Thinking Talk (youtube) #

Talk details from Frank Harrell’s blog - includes slides

This beautiful talk about Bayesian Thinking by Frank Harrell should be essential material for scientists who are trained in frequentist methods. The talk covers the shortcomings of frequentist approaches, but more importantly the paths out of those quagmires are also shown.

Frank discusses his journey to Bayesian stats in this blog post from 2017 which is also in the next section.