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Algorithms Illuminated (Part 3)

- Greedy Algorithms and Dynamic Programming

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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  • Språk:
  • Engelsk
  • ISBN:
  • 9780999282946
  • Bindende:
  • Paperback
  • Sider:
  • 230
  • Utgitt:
  • 9. mai 2019
  • Dimensjoner:
  • 229x153x11 mm.
  • Vekt:
  • 338 g.
  • BLACK NOVEMBER
Leveringstid: 2-4 uker
Forventet levering: 8. desember 2024

Beskrivelse av 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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