Mar 22, 2024
It was a few years ago when I stumbled upon calculator dot net and thought this is so simple & the traffic is insane.…
Mar 11, 2024
Neural network regression is a machine learning technique used for solving regression problems. In regression tasks, the goal is to predict a continuous numeric…
Mar 11, 2024
The Bayesian vs Frequentist debate is one of those academic arguments that I find more interesting to watch than engage in. Rather than enthusiastically jump in…
Mar 11, 2024
Randomized experiments, a.k.a. AB tests, are the established standard in the industry to estimate causal effects. Randomly assigning the treatment (new product, feature, UI, …)…
Mar 11, 2024
If you’ve ever felt a bit intimidated by the world of statistics, especially Bayesian statistics, you’re not alone. But fear not! In this article,…
Mar 11, 2024
There are many ways in which an artificial neural network (ANN) can break down and not perform well. In this blog, we go through…
Mar 11, 2024
consider a function f that is inaccessible to us. We cannot directly access f or compute its gradients. Our only available information is providing an input x and receiving a…
Mar 10, 2024
Introduction to Bayesian Inference Bayesian inference serves as the theoretical backbone of Bayesian Model Fitting, grounded in the concept of updating our beliefs in…
Mar 10, 2024
If someone says, “I believe in science”, what do you think of this statement? Initially, I found it funny because science is not something…
Mar 10, 2024
Optimizing a function is super important in many of the real life analytics use cases. By optimization we mean, either find an maximum or…
Mar 10, 2024
I have a master's degree in physics and work as an aerospace engineering researcher. Physics and engineering are two distinct sciences that share a desire to understand nature…
Mar 5, 2024
In the realm of artificial intelligence and machine learning, neural networks have emerged as a dominant paradigm for solving complex tasks, from image recognition…