ML & Data Science

44 articles in this topic

Natural Language Processing in AI: Core Concepts, a Worked Bigram Example, and How Exams Test It

Build NLP from tokens to transformers, then reproduce the TF-IDF and bigram calculations that exam and placement questions expect.

Updated 7 Aug 20266 min readML & Data Science

Multi Agent Systems in AI: Concepts, Nash Equilibrium and Auctions with Worked Examples

Learn the complete MAS concept set, then compute a Nash equilibrium, a minimax choice and a Vickrey auction outcome step by step.

Updated 4 Aug 20266 min readML & Data Science

Artificial Neural Networks: Complete Guide with Worked Examples for GATE and Interviews

Turn ANN diagrams into numbers. Work through a neuron, activation derivatives, OR and XOR, one gradient update, backpropagation and parameter counts.

Updated 2 Aug 20267 min readML & Data Science

Genetic Algorithms in AI: Complete Guide with a Worked One-Generation Example

Learn the complete genetic algorithm loop, then calculate selection, crossover, mutation, and fitness improvement by hand on a four-chromosome population.

Updated 30 Jul 20266 min read126 viewsML & Data Science

Game Playing in AI: Minimax, Alpha-Beta Pruning, and How Exams Test Them

Build the full game-playing AI toolkit through one tree solved first with minimax and then alpha-beta pruning, plus evaluation functions, chance nodes, and exam traps.

Updated 27 Jul 20266 min read60 viewsML & Data Science

Fuzzy Sets in Artificial Intelligence: Membership Functions, Operations, and Worked Examples

Learn fuzzy sets through one age-based example, from membership grades and alpha-cuts to max-min relation composition. Includes exact exam traps and revision rules.

Updated 25 Jul 20266 min readML & Data Science

Artificial Intelligence for GATE: Syllabus Areas, Weightage Pattern and Prep Order

AI is tested through the GATE DA paper, not as a section of GATE CS. See what to study, how recent papers have distributed marks, and which order avoids rework.

Updated 22 Jul 20265 min readML & Data Science

Approaches to AI: The Four Approaches, a Worked Rational-Agent Example, and How Exams Test Them

Separate the four classic approaches to AI, score a rational vacuum agent step by step, and learn the distinctions that matter in exams and interviews.

Updated 26 Jul 20265 min read102 viewsML & Data Science