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Mastering Algorithms with Python

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Mastering Algorithms with Python
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31,50 EUR
Typical price417,70 PLN
Lowest (90 days)11,22 PLN
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2026-08-07 2026-08-08
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2026-08-0711,22
2026-08-0828,46
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SP SpringerNatureLink Shop INT 31,50 EUR free 31,50 EUR Tillgänglig för 22 timmar sedan View offer
SP Springer Nature Author 5 433,00 JPY 25,00 JPY 5 458,00 JPY Tillgänglig för 8 timmar sedan View offer
VI VitalSource 227,70 ZAR 19,00 ZAR 246,70 ZAR Tillgänglig för 1 dag sedan View offer

Priser och tillgänglighet kan ändras. Senast uppdaterad: 08.08.2026 05:31.

EAN 9798868817984
Springer Nature
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Gain a solid understanding of algorithms and improve your problem-solving abilities using Python code. With practical examples and clear explanations, this book bridges the gap between dense academic texts and overly simple industry guides. Focusing on the logic behind essential algorithms such as Breadth First Search (BFS), Depth First Search (DFS), Divide-and-Conquer, Greedy Methods, and Dynamic Programming, the book provides ample examples, from easy to more advanced. By connecting these concepts to real-world examples, such as chess strategies and the Seam Carving, the book helps readers better grasp and apply algorithms. Each chapter also includes fully implemented Python code, making it a practical reference. Mastering Algorithms with Python is ideal for IT professionals looking to enhance their skills and approach algorithms with clarity and confidence. What You Will Learn · Understand foundational algorithms such as BFS, DFS, Divide-and-Conquer, Greedy Methods, Dynamic Programming through practical examples · Implement algorithms in Python with step-by-step guidance and fully functional code for future reference · Build a solid foundation in advanced concepts such as Minimum Spanning Trees, Fast Fourier Transform, and Monte Carlo Tree Search · Quickly review Python essentials, including data types, flow control, generators, decorators, and classes to enhance your algorithmic understanding Who This Book Is For Software developers, data scientists, machine learning professionals and any curious learners about computer algorithms.

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