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Algorithms Illuminated (Part 3)

- Greedy Algorithms and Dynamic Programming

Bag om Algorithms Illuminated (Part 3)

Algorithms are the heart and soul of computer science. Their applications range from network routing and computational genomics to public-key cryptography and machine learning. Studying algorithms can make you a better programmer, a clearer thinker, and a master of technical interviews. Algorithms Illuminated is an accessible introduction to the subject for anyone with at least a little programming experience. The exposition emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details---like a transcript of what an expert algorithms tutor would say over a series of one-on-one lessons. Part 3 covers greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, shortest paths, optimal search trees).

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9780999282946
  • Indbinding:
  • Paperback
  • Sideantal:
  • 230
  • Udgivet:
  • 9. maj 2019
  • Størrelse:
  • 229x153x11 mm.
  • Vægt:
  • 338 g.
Leveringstid: 8-11 hverdage
Forventet levering: 16. januar 2025

Beskrivelse af Algorithms Illuminated (Part 3)

Algorithms are the heart and soul of computer science. Their applications range from network routing and computational genomics to public-key cryptography and machine learning. Studying algorithms can make you a better programmer, a clearer thinker, and a master of technical interviews. Algorithms Illuminated is an accessible introduction to the subject for anyone with at least a little programming experience. The exposition emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details---like a transcript of what an expert algorithms tutor would say over a series of one-on-one lessons. Part 3 covers greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, shortest paths, optimal search trees).

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