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A common-sense guide to data structures and algorithms : level up your core programming skills / Jay Wengrow.

By: Material type: TextTextPublication details: Raleigh, North Carolina : The Pragmatic Book, c2020.Edition: Second EditionDescription: xviii, 483 pages : illustrations ; 24 cmISBN:
  • 9781680507225
Subject(s): LOC classification:
  • QA 76.9.D35 .W46 2020 c.1
Contents:
Part 1. Why data structure matter.--Part 2. Why algorithms matter.--Part 3. O yes! Big o notation.--Part 4. Speeding up your code with big o.--Part 5. Optimizing code with and without big o.--Part 6. Optimizing for optimistic scenario.--Part 7. Big O in everyday.--Part 8. Blazing fast lookup with hash tables.--Part 9. Crafting elegant code with stacks and queues.--Part 10. Reecursiveley recurse with recursion.--Part 11. Learning to write in recursive.--Part 12. Dynamic programming.--Part 13. Recursive algorithms for speed.--Part 14. Node-based data structures.--Part 15. Speeding up all the things with binary search trees.--Part 16. Keeping your priorities straight with heaps.--Part 17. It doesn't hurt to tries.--Part 18. Connecting everything with graphs.--Part 19. Dealing with space constraints.--Part 20. Techniques for code optimization.
Summary: Take a practical approach to data structures and algorithms, using techniques and real-world scenarios in JavaScript, Python, and Ruby that you can put into production right away. This new and revised second edition features new chapters on recursion, dynamic programming, and using Big O in your daily work.
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Item type Current library Home library Collection Shelving location Call number Copy number Status Date due Barcode
Books Books NU BALIWAG NU BALIWAG Information Technology General Circulation GC QA 76.9.D35 .W46 2020 c.1 (Browse shelf(Opens below)) c.1 Available NUBUL000005215

Includes index.

Part 1. Why data structure matter.--Part 2. Why algorithms matter.--Part 3. O yes! Big o notation.--Part 4. Speeding up your code with big o.--Part 5. Optimizing code with and without big o.--Part 6. Optimizing for optimistic scenario.--Part 7. Big O in everyday.--Part 8. Blazing fast lookup with hash tables.--Part 9. Crafting elegant code with stacks and queues.--Part 10. Reecursiveley recurse with recursion.--Part 11. Learning to write in recursive.--Part 12. Dynamic programming.--Part 13. Recursive algorithms for speed.--Part 14. Node-based data structures.--Part 15. Speeding up all the things with binary search trees.--Part 16. Keeping your priorities straight with heaps.--Part 17. It doesn't hurt to tries.--Part 18. Connecting everything with graphs.--Part 19. Dealing with space constraints.--Part 20. Techniques for code optimization.

Take a practical approach to data structures and algorithms, using techniques and real-world scenarios in JavaScript, Python, and Ruby that you can put into production right away. This new and revised second edition features new chapters on recursion, dynamic programming, and using Big O in your daily work.

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