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Data Structures and Algorithms with the C++ STL. A guide for modern C++ practitioners

John Farrier

While the Standard Template Library (STL) offers a rich set of tools for data structures and algorithms, navigating its intricacies can be daunting for intermediate C++ developers without expert guidance. This book offers a thorough exploration of the STL’s components, covering fundamental data structures, advanced algorithms, and concurrency features.Starting with an in-depth analysis of the std::vector, this book highlights its pivotal role in the STL, progressing toward building your proficiency in utilizing vectors, managing memory, and leveraging iterators. The book then advances to STL’s data structures, including sequence containers, associative containers, and unordered containers, simplifying the concepts of container adaptors and views to enhance your knowledge of modern STL programming. Shifting the focus to STL algorithms, you’ll get to grips with sorting, searching, and transformations and develop the skills to implement and modify algorithms with best practices. Advanced sections cover extending the STL with custom types and algorithms, as well as concurrency features, exception safety, and parallel algorithms.By the end of this book, you’ll have transformed into a proficient STL practitioner ready to tackle real-world challenges and build efficient and scalable C++ applications.

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Data Structures and Program Design Using C++. A Self-Teaching Introduction to Data Structures and C++

Mercury Learning and Information, D. Malhotra, N....

This book introduces the fundamentals of data structures using C++ in a self-teaching format. It covers managing large amounts of information, SEO, and creating Internet/Web indexing services. Practical analogies with real-world applications help explain technical concepts. The book includes end-of-chapter exercises such as programming tasks, theoretical questions, and multiple-choice quizzes.The course starts with an introduction to data structures and the C++ language, progressing through arrays, linked lists, queues, searching and sorting, stacks, trees, multi-way search trees, hashing, files, and graphs. Each chapter builds on the previous one, ensuring a comprehensive understanding of data structures.Understanding these concepts is crucial for managing large databases and optimizing web services. This book guides readers from basic to advanced data structure techniques, blending theoretical knowledge with practical skills. Companion files with source code and data sets enhance the learning experience, making this book an essential resource for mastering data structures with C++.

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Data Structures and Program Design Using Java. A Self-Teaching Introduction to Data Structures and Java

Mercury Learning and Information, D. Malhotra, N....

This book introduces the fundamentals of data structures using Java in a self-teaching format. It covers managing large databases, effective SEO, and creating web indexing services. Real-world analogies help explain technical concepts. Each chapter includes programming tasks, theoretical questions, and multiple-choice quizzes.The course begins with an introduction to data structures and Java, moving through arrays, linked lists, queues, searching and sorting, stacks, trees, multi-way search trees, hashing, files, and graphs. Each chapter builds on the previous one, ensuring a thorough understanding of data structures.Understanding these concepts is crucial for managing information and optimizing web services. This book guides readers from basic to advanced techniques, blending theory with practical skills. It is an essential resource for mastering data structures with Java, enhanced by end-of-chapter exercises and real-world examples.

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Data Structures and Program Design Using Python. A Self-Teaching Introduction to Data Structures and Python

Mercury Learning and Information, D. Malhotra, N....

This book, part of the Pocket Primer series, introduces the basic concepts of data science using Python 3 and other applications. It offers a fast-paced introduction to data analytics, statistics, data visualization, linear algebra, and regular expressions. The book features numerous code samples using Python, NumPy, R, SQL, NoSQL, and Pandas. Companion files with source code and color figures are available.Understanding data science is crucial in today's data-driven world. This book provides a comprehensive introduction, covering key areas such as Python 3, data visualization, and statistical concepts. The practical code samples and hands-on approach make it ideal for beginners and those looking to enhance their skills.The journey begins with working with data, followed by an introduction to probability, statistics, and linear algebra. It then delves into Python, NumPy, Pandas, R, regular expressions, and SQL/NoSQL, concluding with data visualization techniques. This structured approach ensures a solid foundation in data science.

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Deep Reinforcement Learning Hands-On. Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more

Oleg Vasilev, Maxim Lapan, Martijn van Otterlo,...

Deep Reinforcement Learning Hands-On is a comprehensive guide to the very latest DL tools and their limitations. You will evaluate methods including Cross-entropy and policy gradients, before applying them to real-world environments. Take on both the Atari set of virtual games and family favorites such as Connect4.The book provides an introduction to the basics of RL, giving you the know-how to code intelligent learning agents to take on a formidable array of practical tasks. Discover how to implement Q-learning on 'grid world' environments, teach your agent to buy and trade stocks, and find out how natural language models are driving the boom in chatbots.

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Everyday data structures. A practical guide to learning data structures simply and easily

William Smith

Explore a new world of data structures and their applications easily with this data structures book. Written by software expert William Smith, you?ll learn how to master basic and advanced data structure concepts. ? Fully understand data structures using Java, C and other common languages ? Work through practical examples and learn real-world applications ? Get to grips with data structure problem solving using case studies

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Flowchart and Algorithm Basics. Learn the Art of Programming through this Guide to Selection, Looping, Arrays, and File Processing

Mercury Learning and Information, A. B. Chaudhuri

This book equips readers with efficient, well-structured program logics using flowcharts and algorithms. Flowcharting helps create sequences of steps to solve problems through arithmetic and logical manipulations, essential for instructing computers. Applied examples from various subjects encourage readers to grasp the logic leading to solid programming basics.The course begins with an introduction to programming, moving on to problems involving selection, looping, and arrays. It concludes with the art of file processing. Each chapter builds on the previous one, ensuring a comprehensive understanding of programming logic and flowcharting techniques.Understanding these concepts is crucial for developing effective computer instructions. This book transitions readers from basic to advanced problem-solving skills, combining theoretical knowledge with practical examples. It is an essential resource for mastering programming logic and flowcharting.

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Getting Started with Python. Understand key data structures and use Python in object-oriented programming

Fabrizio Romano, Benjamin Baka, Dusty Phillips

This Learning Path helps you get comfortable with the world of Python. It starts with a thorough and practical introduction to Python. You’ll quickly start writing programs, building websites, and working with data by harnessing Python's renowned data science libraries. With the power of linked lists, binary searches, and sorting algorithms, you'll easily create complex data structures, such as graphs, stacks, and queues. After understanding cooperative inheritance, you'll expertly raise, handle, and manipulate exceptions. You will effortlessly integrate the object-oriented and not-so-object-oriented aspects of Python, and create maintainable applications using higher level design patterns. Once you’ve covered core topics, you’ll understand the joy of unit testing and just how easy it is to create unit tests.By the end of this Learning Path, you will have built components that are easy to understand, debug, and can be used across different applications.This Learning Path includes content from the following Packt products:• Learn Python Programming - Second Edition by Fabrizio Romano• Python Data Structures and Algorithms by Benjamin Baka• Python 3 Object-Oriented Programming by Dusty Phillips