Category: Blog
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How to Learn Game-Search Algorithms: Minimax, Alpha–Beta Pruning, Evaluation Functions and Monte Carlo Tree Search
A beginner-to-professional learning manual for game-search algorithms: minimax, alpha–beta pruning, move ordering, evaluation functions, iterative deepening, transpositions, expectimax and Monte Carlo Tree Search.
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How to Learn SAT-Solving Algorithms: DPLL, Unit Propagation, Clause Learning and Modern CDCL
A beginner-to-professional learning manual for SAT solving: CNF, DPLL, unit propagation, conflicts, CDCL, learned clauses, backjumping, watched literals, proof checking and solver practice.
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How to Learn Range-Query Algorithms: Fenwick Trees, Segment Trees, Lazy Propagation and Choosing the Right Structure
A beginner-to-professional learning manual for range-query algorithms: prefix sums, Fenwick trees, segment trees, lazy propagation, invariants, complexity and workload-driven structure choice.
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How to Learn Linear Programming Algorithms: Feasible Regions, Simplex, Duality and Numerical Reality
A beginner-to-professional learning manual for linear programming: model objectives and constraints, reason about feasible regions, trace simplex pivots, understand duality, recognise degeneracy and unboundedness, and evaluate numerical solvers responsibly.
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How to Learn the Fast Fourier Transform: DFT Structure, Divide-and-Conquer, Butterflies and Convolution
A beginner-to-professional learning manual for the Fast Fourier Transform: understand the DFT, expose even–odd structure, trace butterflies, derive O(n log n), connect FFT to convolution, and test numerical behaviour.
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How to Learn Bipartite Matching Algorithms: Augmenting Paths, Hopcroft–Karp and Assignment
A beginner-to-professional learning manual for bipartite matching: model two-sided assignment problems, trace augmenting paths, understand Hopcroft–Karp, distinguish matching from flow, and reason about correctness and workload fit.
