Automatic Differentiation AD is an important algorithm for calculating the derivatives of arbitrary functions that can be expressed by a computer program. One of my favorite CS papers is quot;Automatic differentiation in machine learning: a survey quot; by Baydin, Perlmutter, Radul and Siskind ...

   quot;Dr. Euler’s Fabulous Formula quot; by Paul J. Nahin a kind of sequel to the previous book I read by this author quot;An imaginary tale quot; . Here he collected all the interesting mathematical explorations that didn’t make the cut for that book. I found this one to be much closer to a ...

   This is Part in a series of posts describing the Raft distributed consensus algorithm and its complete implementation in Go. Here is a list of posts in the series: Part : Introduction Part : Elections Part : Commands and log replication Part : Persistence and optimizations Part : Key ...

   In the previous post I talked about running ML inference in Go through a Python sidecar process. In this post, let’s see how we can accomplish the same tasks without using Python at all. How ML models are implemented Let’s start with a brief overview of how ML models are ...

   Machine learning models are rapidly becoming more capable; how can we make use of these powerful new tools in our Go applications For top of the line commercial LLMs like ChatGPT, Gemini or Claude, the models are exposed as language agnostic REST APIs. We can hand craft HTTP requests or use client...