Feb 27 · 16 min read · Week 17 of my data science internship at DataraFlow was dedicated entirely to classification: three algorithms, six datasets, and a repeated outcome that forced me to think harder than any misclassifi
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Feb 10 · 6 min read · 1. Introduction: In the contemporary financial landscape, the decision-making process for credit approval has shifted from subjective human assessment to high-fidelity algorithmic intelligence. Imagine a scenario where a borrower's financial future i...
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Dec 19, 2025 · 4 min read · Today, I started a fun beginner-level project on SMS Spam Classification. The objective of this project was to build an end-to-end text classification pipeline, starting from raw data exploration to model deployment. Dataset Preparation and Cleaning ...
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Oct 25, 2025 · 4 min read · Machine Learning algorithms come in all forms where some rely on distances, some on trees, and some on probabilities. Naive Bayes Classifier belongs to the last group as it predicts categories based on probability and prior knowledge. Let’s understan...
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Oct 14, 2025 · 2 min read · 📖 Naive Bayes is a probabilistic machine learning algorithm based on Bayes’ Theorem. It predicts outcomes by calculating the probability of different classes, assuming all features are independent. Despite this “naive” assumption, it performs surpri...
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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 discussionJul 15, 2025 · 3 min read · "Don’t underestimate simple models. Naive Bayes wins by speed and simplicity."— Tilak Savani 🧠 Introduction Naive Bayes is a supervised learning algorithm based on Bayes’ Theorem — a fundamental rule in probability. Despite its simplicity, it per...
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Jun 29, 2025 · 3 min read · This article introduces the Naive Bayes classifier, a probabilistic algorithm widely used for text classification tasks, particularly when efficiency and simplicity are important. As part of a broader exploration of algorithms for emotion classificat...
Join discussionJun 15, 2025 · 2 min read · Naive Bayes are a set of Supervised machine learning algorithms based on applying Bayes’ theorem with the “naive” assumption of conditional independence between every pair of features given the value of the class variable. Bayes’ theorem states the f...
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