book

Grokking Algorithms, Second Edition

by Aditya Bhargava

March 2024

Beginner to intermediate

320 pages

7h 6m

English

Manning Publications

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forewordprefaceacknowledgmentsabout this bookabout the author
Binary searchBig O notationRecap
How memory worksArrays and linked listsWhich is used more, arrays or linked lists?Selection sortExample code listingRecap
RecursionBase case and recursive caseThe stackRecap

Divide and conquerQuicksortBig O notation revisitedRecap
Hash functionsUse casesCollisionsPerformanceRecap
Introduction to graphsWhat is a graph?Breadth-first searchImplementing the graphImplementing the algorithmRecap
Your first treeA space odyssey: Depth-first searchBinary treesHuffman codingRecap
A balancing actShorter trees are fasterAVL trees: A type of balanced treeSplay treesB-treesRecap
Working with Dijkstra’s algorithmTerminologyTrading for a pianoNegative-weight edgesImplementationRecap
The classroom scheduling problemThe knapsack problemThe set-covering problemRecap
The knapsack problem (revisited)Knapsack problem FAQLongest common substringRecap
Classifying oranges vs. grapefruitBuilding a recommendations systemRegressionIntroduction to machine learningA high-level overview of training an ML modelRecap
Linear regressionInverted indexesThe Fourier transformParallel algorithmsmap/reduceBloom filters and HyperLogLogHTTPS and the Diffie–Hellman key exchangeLocality-sensitive hashingMin heaps and priority queuesLinear programmingEpilogue
Decision problemsThe satisfiability problemHard to solve, quick to verifyReductionsNP-hardNP-completeRecap

Content preview from Grokking Algorithms, Second Edition

front matter

foreword

More people than ever need to learn how to program. Sure, some people literally program for their jobs (software engineers or web developers, for example). But many other jobs, not historically requiring programming, have a programming component now or will in the future. Programming also helps people understand the technological world in which they live.

Unfortunately, the benefits of programming are not equally distributed. In North American computer science (CS) programs, for example, we have a very low participation of women and some ethnic/racial groups. It’s critical that we be able to expand programming and CS to a more diverse group. The solution will involve making progress on a number of fronts, including overcoming ...