99 Advanced Algorithms Handbook With Python
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99 Advanced Algorithms Handbook With Python
Author: Jamie Flux
language: en
Publisher: Independently Published
Release Date: 2024-11-21
Immerse yourself in a comprehensive exploration of the most pivotal and sophisticated algorithms shaping the landscape of modern programming. This extensive compendium offers seasoned developers and computer scientists a definitive guide to 99 advanced algorithms, each meticulously selected for its significance and practical applications in the field. Structured for both learning and reference, each chapter focuses on a single algorithm, presenting: Concise Explanations: Understand the underlying principles and logic with clear, succinct descriptions that distill complex concepts into accessible insights. Practical Code Implementations: Access ready-to-use code snippets written in clean, efficient syntax, designed to integrate seamlessly into your projects and research. Applications and Use Cases: Discover how each algorithm applies to real-world problems across domains such as data compression, cryptography, machine learning, computational geometry, and network optimization. By bridging theory and practice, this compendium not only enhances your algorithmic repertoire but also sharpens your problem-solving skills. Whether optimizing existing systems or pioneering new solutions, you'll find the tools and knowledge to advance your work to new heights. Elevate your expertise and stay at the forefront of technological innovation with this essential resource-a must-have addition to the professional library of any serious programmer or academic.
99 Aerospace Engineering Algorithms Handbook With Python
Author: Jamie Flux
language: en
Publisher: Independently Published
Release Date: 2024-11-21
Unlock new horizons in aerospace engineering with this comprehensive guide to advanced programming algorithms-all meticulously implemented in Python. Spanning 99 detailed chapters, this authoritative volume is an indispensable resource for engineers, researchers, and students aiming to propel their understanding and application of cutting-edge computational methods. Key Features: In-Depth Exploration of Complex Algorithms: Dive into sophisticated topics such as high-fidelity computational fluid dynamics, orbital mechanics, aeroelasticity, and hypersonic flow simulations. Each chapter provides a deep dive into a specific algorithm, complete with mathematical foundations and practical applications. Python Implementations: Benefit from fully functional Python code examples that bring each algorithm to life. Learn how to implement, customize, and optimize these algorithms for your own projects. Interdisciplinary Applications: Discover how advanced algorithms can be applied across various domains, including propulsion system modeling, guidance and control systems, machine learning in aerospace applications, and more. Real-World Problem Solving: Equip yourself with tools and techniques to address real-world aerospace challenges. From aerodynamic shape optimization to satellite attitude control, this book bridges the gap between theory and practice. Cutting-Edge Techniques: Stay ahead of the curve with the latest methodologies in adaptive control, computational aeroacoustics, multidisciplinary design optimization, and artificial intelligence applications in aerospace. Whether you're developing next-generation aircraft, designing intricate space missions, or conducting advanced research, this book provides the essential algorithms and programming techniques to advance your work. Harness the power of Python to drive innovation, optimize performance, and contribute to the future of aerospace engineering. Elevate your expertise and become a catalyst for innovation in the aerospace sector with this essential programming algorithm guide.
Advanced Algorithms and Data Structures
Author: Marcello La Rocca
language: en
Publisher: Simon and Schuster
Release Date: 2021-08-10
"An accessible introduction to the fundamental algorithms used to run the world." - Richard Vaughan, Purple Monkey Collective 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