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Python Data Structures Pocket Primer. A concise guide to Python data structures to enhance your skills

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Python Data Structures Pocket Primer. A concise guide to Python data structures to enhance your skills Mercury Learning and Information, Oswald Campesato - okladka książki

Python Data Structures Pocket Primer. A concise guide to Python data structures to enhance your skills Mercury Learning and Information, Oswald Campesato - okladka książki

Serie wydawnicze:
Learning
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
245
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     PDF
     ePub

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This Pocket Primer book introduces the fundamentals of data structures using Python. It provides a comprehensive yet fast-paced introduction to core Python concepts and data structures, emphasizing their importance in managing large datasets and implementing search and sort algorithms effectively. The course starts with a basic introduction to Python, setting a solid foundation for more complex topics.
The journey continues with an exploration of recursion and combinatorics, followed by detailed discussions on strings, arrays, and various search and sort algorithms. Further, the book delves into linked lists, queues, and stacks, illustrating their practical applications with numerous code samples. This structured approach ensures that learners can progressively build their knowledge and skills in data structures, reinforced by hands-on coding examples.
With companion files available for download, the book provides additional resources for practice and deeper understanding. This comprehensive guide is ideal for both beginners and those looking to strengthen their grasp of data structures in Python, equipping them with essential tools for managing and manipulating large datasets.

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O autorach książki

MERCURY LEARNING and INFORMATION publishes content in the areas of science and medicine, technology and computing, engineering, and mathematics designed for the professional/reference, trade, library, higher education, career school, and online training markets.
Oswald Campesato specializes in Deep Learning, Python, Data Science, and generative AI. He is the author/co-author of over forty books including Google Gemini for Python, Data Cleaning, and GPT-4 for Developers (all Mercury Learning).

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