ML & Data Science
44 articles in this topic
Genetic Algorithms Fundamentals: Selection, Crossover, Mutation and a Worked Generation
Decode a five-bit chromosome, calculate roulette probabilities, and follow selection, crossover, mutation and replacement through one complete genetic algorithm generation.
Updated 30 Aug 20265 min read69 viewsML & Data Science
Constraint Satisfaction Problem: Concepts, a Worked Search Trace and Exam Traps
Learn how to model and solve a CSP from zero. Follow one failed scheduling branch, the first valid solution, an AC-3 trace and the ordering rules that make search smaller.
Updated 29 Aug 20266 min readML & Data Science
Multi-Layer Perceptron and Backpropagation Explained with a Worked Example
Build a 2-2-1 neural network from its inputs to its loss, then trace backpropagation through every weight and bias. The complete update shows why each sign matters.
Updated 26 Aug 20265 min read93 viewsML & Data Science
Artificial Neural Networks Explained: Forward Pass, Worked Example and Exam Question Patterns
Build a small 2-2-1 neural network, calculate every value in its forward pass, and learn how activations, loss, training and parameter counts become exam tasks.
Updated 25 Aug 20265 min read50 viewsML & Data Science
Genetic Representation and Encoding: Worked Examples and Exam Traps
Separate genotype, phenotype and fitness, then follow a complete 5-bit example. Learn how feasibility, redundancy, locality and operators shape a genetic search.
Updated 23 Aug 20266 min readML & Data Science
Expert Systems and Uncertainty Explained: Rules, Certainty Factors and Worked Problems
Build an expert system from its core components, trace its rules in both directions, and solve the same pump case using certainty factors, Bayes and fuzzy logic.
Updated 21 Aug 20266 min readML & Data Science
Means–Ends Analysis in AI: Subgoals, a 3-Disk Worked Example and Exam Traps
Learn the exact Means–Ends Analysis operator cycle, follow all seven moves of a 3-disk Tower of Hanoi solution, and avoid common reasoning traps.
Updated 20 Aug 20266 min readML & Data Science
Perceptron and Activation Functions MCQs: 11 Solved Questions
Work through 11 practice problems covering perceptron sums and outputs, sign and sigmoid activation, separating lines, linear separability, and ANN weights.
Updated 18 Aug 20268 min readML & Data Science
Multi-Layer Perceptron and Backpropagation MCQs: Solved with Full Working
Work through perceptron outputs, sigmoid derivatives, an MLP forward pass, gradient descent, and learning-rule updates with every step shown.
Updated 16 Aug 20268 min read58 viewsML & Data Science
AI Agent Architecture and Program Types MCQs: 11 Solved Questions
Eleven solved AI agent MCQs with the trap in each one named: current-percept rules, sensor versus actuator, goal versus utility scoring, and what counts as learning.
Updated 14 Aug 20268 min readML & Data Science
Knowledge Representation in Artificial Intelligence: Logic, Semantic Networks, Frames and Rules with Worked Examples
Learn how AI stores facts and derives new ones through logic, semantic networks, frames and rules. Two worked traces make the inference steps exam-ready.
Updated 11 Aug 20266 min read182 viewsML & Data Science
Search Algorithms in AI: BFS, DFS, UCS and A* Explained on One Worked Graph
Run five major AI search algorithms on the same weighted graph, compare the paths they return, and check admissibility and consistency with real numbers.
Updated 9 Aug 20266 min read103 viewsML & Data Science