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Advanced Algorithms and Data Structures
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Advanced Algorithms and Data Structures teaches you powerful approaches to a wide range of tricky coding challenges that you can adapt and apply to your own applications.
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- Advanced Algorithms and Data Structures introduces a collection of algorithms for complex programming challenges in data analysis, machine learning, and graph computing.Summary As a software engineer, you’ll encounter countless programming challenges that initially seem confusing, difficult, or even impossible. Don’t despair! Many of these “new” problems already have well-established solutions. Advanced Algorithms and Data Structures teaches you powerful approaches to a wide range of tricky coding challenges that you can adapt and apply to your own applications. Providing a balanced blend of classic, advanced, and new algorithms, this practical guide upgrades your programming toolbox with new perspectives and hands-on techniques. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Can you improve the speed and efficiency of your applications without investing in new hardware? Well, yes, you can: Innovations in algorithms and data structures have led to huge advances in application performance. Pick up this book to discover a collection of advanced algorithms that will make you a more effective developer. About the book Advanced Algorithms and Data Structures introduces a collection of algorithms for complex programming challenges in data analysis, machine learning, and graph computing. You’ll discover cutting-edge approaches to a variety of tricky scenarios. You’ll even learn to design your own data structures for projects that require a custom solution. What's inside Build on basic data structures you already know Profile your algorithms to speed up application Store and query strings efficiently Distribute clustering algorithms with MapReduce Solve logistics problems using graphs and optimization algorithms About the reader For intermediate programmers. About the author Marcello La Rocca is a research scientist and a full-stack engineer. His focus is on optimization algorithms, genetic algorithms, machine learning, and quantum computing. Table of Contents 1 Introducing data structures PART 1 IMPROVING OVER BASIC DATA STRUCTURES 2 Improving priority queues: d-way heaps 3 Treaps: Using randomization to balance binary search trees 4 Bloom filters: Reducing the memory for tracking content 5 Disjoint sets: Sub-linear time processing 6 Trie, radix trie: Efficient string search 7 Use case: LRU cache PART 2 MULTIDEMENSIONAL QUERIES 8 Nearest neighbors search 9 K-d trees: Multidimensional data indexing 10 Similarity Search Trees: Approximate nearest neighbors search for image retrieval 11 Applications of nearest neighbor search 12 Clustering 13 Parallel clustering: MapReduce and canopy clustering PART 3 PLANAR GRAPHS AND MINIMUM CROSSING NUMBER 14 An introduction to graphs: Finding paths of minimum distance 15 Graph embeddings and planarity: Drawing graphs with minimal edge intersections 16 Gradient descent: Optimization problems (not just) on graphs 17 Simulated annealing: Optimization beyond local minima 18 Genetic algorithms: Biologically inspired, fast-converging optimization
| Publisher | Manning |
| Publication date | June 29, 2021 |
| Language | English |
| Print length | 768 pages |
| ISBN-10 | 1617295485 |
| ISBN-13 | 978-1617295485 |
| Item Weight | 2 pounds (910 grams) |
| Dimensions | 7.38 x 1.5 x 9.25 inches (18.7 x 3.8 x 23.5 cm) |
À qui est-ce destiné ?
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Aspiring Developers
This product offers crucial knowledge for aspiring developers seeking to enhance their programming and problem-solving skills.
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Computer Science Students
Ideal for CS students, it provides a comprehensive understanding of algorithms and data structures essential for coursework.
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Interview Preparers
Perfect for those preparing for technical interviews, as it covers commonly asked algorithm questions and problem-solving techniques.
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Casual Learners
Not suitable for casual learners who prefer light reading without the need for deep technical understanding.
DESCRIPTION DU PRODUIT
Questions et réponses des clients
-
question:
What are Advanced Algorithms and Data Structures?
répondre: Advanced Algorithms and Data Structures refer to complex methodologies and frameworks used to solve computational problems efficiently. This encompasses a range of concepts including graph algorithms, dynamic programming, tree structures, and more. Understanding these concepts is crucial for software developers and computer scientists as they provide the foundation for optimal solutions in scenarios like search operations, database management, and real-time processing tasks. -
question:
Who should study Advanced Algorithms and Data Structures?
répondre: Individuals pursuing careers in software development, data science, or computer engineering should definitely study Advanced Algorithms and Data Structures. This knowledge is vital for grappling with large datasets, enhancing application performance, and tackling challenges within coding interviews. Furthermore, academic researchers or students in computer science programs can greatly benefit from a solid grounding in these principles, as they often underpin theoretical and practical applications in technology. -
question:
How do Advanced Algorithms improve software performance?
répondre: Advanced Algorithms are designed to optimize the efficiency of processes by minimizing computation time and resource usage. For example, employing a more sophisticated sorting algorithm can drastically reduce the time taken to organize large datasets. This is crucial in scenarios such as real-time analytics where speed and efficiency are key. Additionally, using the right data structures helps organize data effectively, allowing for quicker access and manipulation during application operations. -
question:
What are some common types of Advanced Data Structures?
répondre: Common Advanced Data Structures include graphs, trees (such as binary trees and AVL trees), heaps, and hash tables. Each structure has its own unique properties and use cases, such as graphs for representing networks, or trees for efficiently managing hierarchical data. Understanding these structures allows developers to choose the best option for their specific problem, leading to optimized data handling and algorithm performance in their applications. -
question:
Can Advanced Algorithms and Data Structures be applied to everyday software development?
répondre: Absolutely! Advanced Algorithms and Data Structures can significantly enhance everyday software development projects. For instance, implementing a priority queue using a heap can improve task scheduling in applications. Similarly, knowledge of graph algorithms can assist in route and pathfinding features in navigation software. Recognizing the right algorithms and structures to use for particular tasks can lead to more robust, swift, and efficient software solutions. -
question:
What resources are recommended for learning Advanced Algorithms and Data Structures?
répondre: To learn Advanced Algorithms and Data Structures, consider exploring online courses from platforms like Coursera or edX, as well as textbooks such as 'Introduction to Algorithms' by Cormen et al. Additionally, engaging with coding challenge websites like LeetCode can provide practical experience. Finding community forums for discussion, like Stack Overflow, can also enhance understanding by allowing you to ask questions and view different perspectives on problem-solving. -
question:
Is programming knowledge required to understand Advanced Algorithms?
répondre: Yes, a fundamental understanding of programming concepts is essential to grasp Advanced Algorithms and Data Structures effectively. Typically, languages like Python, Java, or C++ are used to implement these algorithms, and having a base knowledge in coding practices enhances your ability to apply these concepts in real-world scenarios. Therefore, it is often recommended to have a foundational programming background before diving into advanced topics. -
question:
Are Advanced Algorithms difficult to learn?
répondre: Learning Advanced Algorithms can be challenging, particularly for beginners, due to their complexity and abstract nature. However, with consistent practice and a systematic study approach, they can be made manageable. Starting with the basics of algorithms and data structures before gradually moving to advanced topics is a recommended strategy. Engaging with practical examples, exercises, and projects can also bridge the gap between theory and application, making the learning process smoother. -
question:
What is the difference between algorithms and data structures?
répondre: Algorithms are sets of instructions or procedures for solving problems, while data structures refer to the organization of data to facilitate efficient access and modification. For instance, a sorting algorithm describes how to arrange elements systematically, whereas a data structure like an array or a linked list determines how these elements are stored in memory. Understanding their interplay is crucial, as the choice of data structure can affect the algorithm's efficiency and vice versa. -
question:
Where can I buy Advanced Algorithms and Data Structures in Switzerland?
répondre: You can buy Advanced Algorithms and Data Structures from Ubuy, which offers a wide selection of educational resources, including books and online materials tailored for learning advanced topics in computer science. Ubuy’s extensive inventory ensures that you have access to various formats and options suited to different learning preferences, making it a reliable choice for acquiring these valuable resources in Switzerland.
Structured Design Editorial Review
The "Advanced Algorithms and Data Structures" book has received positive reviews from customers. Many have praised the comprehensive coverage of complex algorithms and data structures, noting that the content is well-organized and easy to understand. The book is appreciated for its clear explanations and practical examples, which make it valuable for both students and professionals in the field. Customers have also commended the author's writing style, stating that it is engaging and keeps the reader engaged throughout. Overall, the Consensus is that this book is a valuable resource for anyone looking to deepen their understanding of advanced algorithms and data structures.
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Avantages
- Comprehensive coverage of complex algorithms and data structures
- Well-organized content and easy to understand
- Clear explanations and practical examples
- Suitable for both students and professionals
- Engaging writing style
Les inconvénients
- No specific criticisms mentioned
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Caractéristiques et avantages
- Introduces a collection of algorithms for complex programming challenges in data analysis, machine learning
- Includes a blend of classic, advanced, and new algorithms
- Helps in improving application performance without investing in new hardware
- Teaches how to design custom data structures
- For intermediate level programmers
- Written by Marcello La Rocca, a research scientist and a full-stack engineer
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