Math for Programming. Learn the Math, wright better code

ForewordAcknowledgmentsIntroductionChapter 1: Computers and NumbersOptimize storage, perform arithmetic operations, and prevent overflow or precision errorsChapter 2: Sets and Abstract AlgebraData structures, cryptography, error detection and correction, and algorithm designChapter 3: Boolean AlgebraLogic gates as well as conditional statement, control structure, and algorithm developmentChapter 4: Functions and RelationsDefine algorithms, understand dependencies between data, and design software componentsChapter 5: InductionProve algorithm correctness, particularly those that involve recursion or iterative processesChapter 6: Recurrence and RecursionAlgorithm performance and problem-solvingChapter 7: Number TheoryCryptography, hash functions, and efficient algorithm developmentChapter 8: Counting and CombinatoricsAnalyze algorithm complexity and resource allocation, and solve permutation and probability problemsChapter 9: GraphsNetwork design, route optimization, connectivity solutions, and model relationshipsChapter 10: TreesEssential for efficient searching, sorting, and parsing operationsChapter 11: ProbabilityModel uncertainty, manage risk, and develop algorithms for randomized processesChapter 12: StatisticsData analysis, model validation, decision-making, and machine learning algorithm developmentChapter 13: Linear AlgebraComputer graphics algorithms, machine learning models, and scientific computationsChapter 14: Differential CalculusOptimize functions, model change, and develop ML algorithms for training modelsChapter 15: Integral CalculusCompute areas under curves, solve differential equations, and model continuous processesChapter 16: Differential EquationsModel and solve problems related to change and dynamic systemsIndex