A common-sense guide to data structures and algorithms : level up your core programming skills / Jay Wengrow ; edited by Brian MacDonald
By: Wengrow, Jay [author].
Contributor(s): MacDonald, Brian [editor].
Series: Pragmatic programmers.Publisher: Raleigh, North Carolina : The Pragmatic Bookshelf, ©2020Copyright date: ©2020Edition: Second edition.Description: 481 p: illustrations ; 24 cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 9781680507225; 1680507222.Subject(s): Data structures (Computer science) | Computer algorithmsGenre/Form: Print books.| Current location | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|
| On Shelf | QA76.9 .D35 2020 (Browse shelf) | Available | AU00000000017715 |
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| QA76.9.D343 V76 2019 Big data analytics for large-scale multimedia search / | QA76.9.D343 Y4 2014 Data mining : theories, algorithms, and examples / | QA76.9.D343 Z35 2014 Data mining and analysis fundamental concepts and algorithms / | QA76.9 .D35 2020 A common-sense guide to data structures and algorithms : level up your core programming skills / | QA76.9.D35 K558 2016 Basic concepts in data structures / | QA76.9.D35 N38 2016 Compact data structures : a practical approach / | QA76.9 .D35 W46 2017 A common-sense guide to data structures and algorithms : level up your core programming skills / |
Previous edition: 2017
Includes index
Why data structures matter -- Why algorithms matter -- O yes! Big O notation -- Speeding up your code with Big O -- Optimizing code with and without Big O -- Optimizing for optimistic scenarios -- Big O in everyday code -- Blazing fast lookup with hash tables -- Crafting elegant code with stacks and queues -- Recursively recurse with recursion -- Learning to write in recursive -- Dynamic programming -- Recursive algorithms for speed -- Node-based data structures -- Speeding up all the things with binary search trees -- Keeping your priorities straight with heaps -- It doesn't hurt to trie -- Connecting everything with graphs -- Dealing with space constraints -- 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