ML & Data Science
23 articles in this topic
Genetic Operators: Crossover and Mutation with Worked Examples and Exam Traps
Trace binary crossover and bit-flip mutation step by step, then see how order crossover and swap mutation keep a route permutation valid.
Fuzzy Systems and Inference Models: Membership Functions, Mamdani vs Sugeno, and a Worked Example
Learn how a fuzzy inference system turns crisp inputs into one useful output. Compare Mamdani, Sugeno, and Tsukamoto, then calculate a four-rule fan controller step by step.
Fuzzy Relations and Composition: Max-Min Concepts and a Worked Example
Learn how to read a fuzzy relation, form its inverse and alpha-cuts, and compute max-min composition cell by cell. The same matrices reveal common operator and transitivity traps.
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.
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.
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.
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.
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.
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.
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.
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.
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.