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What is this?
A large collection of JavaScript implementations of classic algorithms and data structures, where each one has its own folder with code, tests, and a README explaining the theory and further reading links.
A large collection of JavaScript implementations of classic algorithms and data structures, where each one has its own folder with code, tests, and a README explaining the theory and further reading links.Is this a library I can import, or a learning resource?It is primarily an educational reference rather than an installable npm package - every algorithm lives in its own folder with source code, tests, and an explanatory README, meant to be read and studied rather than pulled in as a dependency.
It is primarily an educational reference rather than an installable npm package - every algorithm lives in its own folder with source code, tests, and an explanatory README, meant to be read and studied rather than pulled in as a dependency.How do I run the examples and tests?Clone the repo and run npm install to pull dependencies, then npm run test to execute the Jest suite or npm run lint to check code quality with ESLint; you can also run a single test by name.
Clone the repo and run npm install to pull dependencies, then npm run test to execute the Jest suite or npm run lint to check code quality with ESLint; you can also run a single test by name.Do I need a specific Node version?Yes, you need Node 16 or newer (the package.json even specifies Node >=22); if linting or tests fail, delete node_modules and reinstall, and double-check your Node version with nvm.
Yes, you need Node 16 or newer (the package.json even specifies Node >=22); if linting or tests fail, delete node_modules and reinstall, and double-check your Node version with nvm.Is this meant to be used as a dependency in a real project?No - it is built for learning and interview preparation, not as a production library; there is no published package, just per-algorithm source files meant to be read and copied if needed.
No - it is built for learning and interview preparation, not as a production library; there is no published package, just per-algorithm source files meant to be read and copied if needed.How is the content organized?Algorithms are grouped both by topic (math, strings, sorting, graphs, trees, cryptography, etc.) and separately by algorithmic paradigm (brute force, greedy, divide and conquer, dynamic programming, backtracking, branch and bound).
Algorithms are grouped both by topic (math, strings, sorting, graphs, trees, cryptography, etc.) and separately by algorithmic paradigm (brute force, greedy, divide and conquer, dynamic programming, backtracking, branch and bound).Where should a beginner start?Items are labeled B for Beginner (like Linked List, Binary Search, Bubble Sort, Fibonacci Number) or A for Advanced, so beginners should work through the B-tagged topics first.
Items are labeled B for Beginner (like Linked List, Binary Search, Bubble Sort, Fibonacci Number) or A for Advanced, so beginners should work through the B-tagged topics first.Is the content available in languages other than English?Yes, the README has been translated into many languages including Chinese, Korean, Japanese, Polish, French, Spanish, Portuguese, Russian, Turkish, Italian, Indonesian, Ukrainian, Arabic, Vietnamese, German, Uzbek and Hebrew.
Yes, the README has been translated into many languages including Chinese, Korean, Japanese, Polish, French, Spanish, Portuguese, Russian, Turkish, Italian, Indonesian, Ukrainian, Arabic, Vietnamese, German, Uzbek and Hebrew.Does it cover machine learning as well?Yes, it includes basic ML algorithms such as k-NN and k-Means clustering, plus 'NanoNeuron', a tiny example of forward and backward propagation to illustrate how machines learn.
Yes, it includes basic ML algorithms such as k-NN and k-Means clustering, plus 'NanoNeuron', a tiny example of forward and backward propagation to illustrate how machines learn.What are similar projects?algo, algorithms, interviews, algorithm-base, interview, JavaScript, apachecn-algo-zh, hello-algorithm
algo, algorithms, interviews, algorithm-base, interview, JavaScript, apachecn-algo-zh, hello-algorithmWhich topics is it in?tree, algorithms-implemented, sorting-algorithms, coding-interview, leetcode, graph, algorithm, cryptography, interview-questions, data-structures, interview, interview-preparation
tree, algorithms-implemented, sorting-algorithms, coding-interview, leetcode, graph, algorithm, cryptography, interview-questions, data-structures, interview, interview-preparation