Accelerated Linearized Laplace Approximation for Bayesian Deep Learning
Dec 8, 2025 · 10 min read · Introduction Bayesian NNs and Laplace Approximation (LA) Linearized Laplace (LLA) and Scalability Problem Accelerated Linearized Laplace Approximation (ELLA) Experiments Conclusion Introduction Deep neural networks (DNNs) have become the default to...
Join discussionDay 9 – Bayes’ Theorem & Naive Bayes Classifier
Aug 28, 2025 · 2 min read · Hey everyone 👋 Dhairya here, Today’s focus was on one of the most fundamental ideas in probabilistic machine learning: Bayes’ Theorem and its practical use in the Naive Bayes classifier. 🔢 What I Learned Today 1. Bayes’ Theorem Formula: P(A∣B)=...
Join discussionNaive Bayes Classifier —ML Algorithm
Jul 16, 2025 · 4 min read · While watching the tutorial, I was confused. What the heck is this? I got the point about how probability works and the mathematical intuition behind this theorem, but I'm confused about where, when, and why I should use this theorem. And when I trie...
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Probability concepts in real world
May 6, 2025 · 3 min read · Probability can be simply as how likely something is to happen. Whenever we are unsure of the result, we tends toward there is certain chance of this happening. And, the analysis of events governed by probability is called statistics. Here are some r...
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O problema de Monty Hall
Mar 26, 2025 · 5 min read · O artigo do MIT Technology Review, intitulado "O problema de Monty Hall: probabilidade condicional" (https://mittechreview.com.br/o-problema-de-monty-hall/?utm_source=chatgpt.com) explica como o problema ilustra a probabilidade condicional. Em um pro...
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I'll Never Forget Bayes's Theorem Again
Feb 13, 2025 · 11 min read · Mathematical intuition is, as the LLMs say, crucial, to technologists and engineers. We can "chi by eye" or "guesstimate" or even better solve problems with much less effort and error because we know how it works and why it works that way. Bayes's Th...
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Probability and Bayes' Theorem in Machine Learning
Feb 13, 2025 · 3 min read · Introduction Probability theory is a fundamental concept in machine learning, enabling models to make predictions and handle uncertainty in data. One of the most powerful tools in probability is Bayes' Theorem, which provides a mathematical framework...
Join discussionDay 2: Statistics and Probability Basics
Jan 16, 2025 · 5 min read · In this blogpost, we will be amplifying our area of focus on Statistics and Probability, which plays a crucial role in the field of Data Science and Machine Learning. We will also have a look at some of the algorithms and will also look into the prac...
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ML Classification 3.5: Naive Bayes
Nov 4, 2024 · 8 min read · Hello and welcome back to the blog of machine learning. Today we will learn about Bayes theorem. Our main focus for this blog is on naive but we can’t proceed to it without Bayes theorem so here it is. Question Why is this algorithm called the native...
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