Learn Design And Analysis Of Algorithms In 24 Hours
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Learn Design And Analysis Of Algorithms In 24 Hours
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Author : Alex Nordeen
language : en
Publisher: Guru99
Release Date : 2022-07-18
Learn Design And Analysis Of Algorithms In 24 Hours written by Alex Nordeen and has been published by Guru99 this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-18 with Computers categories.
Table Of Content Chapter 1: Greedy Algorithm with Example: What is, Method and Approach What is a Greedy Algorithm? History of Greedy Algorithms Greedy Strategies and Decisions Characteristics of the Greedy Approach Why use the Greedy Approach? How to Solve the activity selection problem Architecture of the Greedy approach Disadvantages of Greedy Algorithms Chapter 2: Circular Linked List: Advantages and Disadvantages What is a Circular Linked List? Basic Operations in Circular Linked lists Insertion Operation Deletion Operation Traversal of a Circular Linked List Advantages of Circular Linked List Disadvantages of Circular Linked List Singly Linked List as a Circular Linked List Applications of the Circular Linked List Chapter 3: Array in Data Structure: What is, Arrays Operations [Examples] What are Arrays? Concept of Array Why do we need arrays? Creating an Array in Python Ways to Declare an Array in Python Array Operations Creating an Array in C++ Array Operations in C++ Array Operations in Java Chapter 4: B TREE in Data Structure: Search, Insert, Delete Operation Example What is a B Tree? Why use B-Tree History of B Tree Search Operation Insert Operation Delete Operation Chapter 5: B+ TREE : Search, Insert and Delete Operations Example What is a B+ Tree? Rules for B+ Tree Why use B+ Tree B+ Tree vs. B Tree Search Operation Insert Operation Delete Operation Chapter 6: Breadth First Search (BFS) Algorithm with EXAMPLE What is BFS Algorithm (Breadth-First Search)? What is Graph traversals? The architecture of BFS algorithm Why do we need BFS Algorithm? How does BFS Algorithm Work? Example BFS Algorithm Rules of BFS Algorithm Applications of BFS Algorithm Chapter 7: Binary Search Tree (BST) with Example What is a Binary Search Tree? Attributes of Binary Search Tree Why do we need a Binary Search Tree? Types of Binary Trees How Binary Search Tree Works? Important Terms Chapter 8: Binary Search Algorithm with EXAMPLE What is Search? What is Binary Search? How Binary Search Works? Example Binary Search Why Do We Need Binary Search? Chapter 9: Linear Search: Python, C++ Example What is Searching Algorithm? What is Linear Search? What does Linear Search Function do? How does Linear Search work? Pseudo Code for Sequential Search Algorithm C++ Code Example Linear Search Python Code Example Linear Search Complexity Analysis of Linear Search Algorithm How to improve Linear Search Algorithm Application of Linear Search Algorithm Chapter 10: Bubble Sort Algorithm with Python using List Example What is a Bubble Sort? Implementing the Bubble Sort Algorithm Optimized Bubble Sort Algorithm Visual Representation Python Examples Code Explanation Bubble sort advantages Bubble sort Disadvantages Complexity Analysis of Bubble Sort Chapter 11: Selection Sort: Algorithm explained with Python Code Example What is Selection Sort? How does selection sort work? Problem Definition Solution (Algorithm) Visual Representation Selection Sort Program using Python 3 Code Explanation Time Complexity Of Selection Sort When to use selection sort? Advantages of Selection Sort Disadvantages of Selection Sort Chapter 12: Hash Table in Data Structure: Python Example What is Hashing? What is a Hash Table? Hash functions Qualities of a good hash function Collision Hash table operations Hash Table Implementation with Python Example Hash Table Code Explanation Python Dictionary Example Complexity Analysis Real-world Applications Advantages of hash tables Disadvantages of hash tables Chapter 13: Tree Traversals (Inorder, Preorder, Postorder): C,Python, C++ Examples What is Tree Traversal? Types of Tree Traversal Breadth-First Traversal Inorder Traversal Bianry Tree Post-Order Traversal Preorder Traversal Implementation in Python: Implementation in C: Implementation of C++ (Using std:queue for level order): Chapter 14: Binary Tree in Data Structure (EXAMPLE) What is a Binary Tree? What are the Differences Between Binary Tree and Binary Search Tree? Example of Binary Search Trees Types of Binary Tree: Implementation of Binary Tree in C and C++: Implementation of Binary Tree in Python Application of Binary Tree: Chapter 15: Combination Algorithm: Print all possible combinations of r | C,C++,Python What is the Combination? The time complexity analysis for Combination Method-1: Fixed element with recursion Method 2 (Include and Exclude every element): Handling Duplicate Combinations Using a dictionary or unordered map to track duplicate combinations Chapter 16: Longest Common Subsequence: Python, C++ Example What is Longest Common Subsequence? Naive Method Optimal Substructure Recursive Method of Longest Comm Sequence Dynamic Programming method of Longest Common Subsequence (LCS) Chapter 17: Dijisktra's Algorithm: C++, Python Code Example What is the shortest path or shortest distance? How Dijkstra’s Algorithm Works Difference Between Dijkstra and BFS, DFS 2D grid demonstration of how BFS works Example of Dijkstra’s Algorithm C++ implementation Dijkstra’s Algorithm Python implementation Dijkstra’s Algorithm Application of Dijkstra Algorithm Limitation of Dijkstra’s Algorithm
The Design And Analysis Of Efficient Learning Algorithms
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Author : Robert E. Schapire
language : en
Publisher: MIT Press (MA)
Release Date : 1992
The Design And Analysis Of Efficient Learning Algorithms written by Robert E. Schapire and has been published by MIT Press (MA) this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Computers categories.
This monograph describes results derived from the mathematically oriented framework of computational learning theory.
Liss 2021
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Author : Xianliang Shi
language : en
Publisher: Springer Nature
Release Date : 2022-01-28
Liss 2021 written by Xianliang Shi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-28 with Business & Economics categories.
This book aims to provide new research methods, theories and applications from various areas of management and engineering. In detail, the included scientific papers analyze and describe communication processes in the fields of logistics, informatics, service sciences and other related areas. The variety of the papers delivers added value for both scholars and practitioners. Information and communication technologies have been providing an effective network infrastructure and development platform for logistics and service operations. To meet the needs of consumers and to promote core competences, many institutions and firms have been developing new types of services. This proceeding focus on “AI and data driven technical and management innovation in logistics, informatics and services.” In detail, the included scientific papers analyze the latest fundamental advances in the state of the art and practice of logistics, informatics, service operations and service science. This book is the documentation of the conference “11th International Conference on Logistics, Informatics and Service Sciences,” which took place at the Shandong University. Due to the impact of COVID-19, LISS 2021 took place online as a virtual conference.
Learning And Intelligent Optimization Designing Implementing And Analyzing Effective Heuristics
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Author : Thomas Stützle
language : en
Publisher: Springer
Release Date : 2009-11-27
Learning And Intelligent Optimization Designing Implementing And Analyzing Effective Heuristics written by Thomas Stützle and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-11-27 with Computers categories.
LION 3, the Third International Conference on Learning and Intelligent Op- mizatioN, was held during January 14–18 in Trento, Italy. The LION series of conferences provides a platform for researchers who are interested in the int- section of e?cient optimization techniques and learning. It is aimed at exploring the boundaries and uncharted territories between machine learning, arti?cial intelligence, mathematical programming and algorithms for hard optimization problems. The considerable interest in the topics covered by LION was re?ected by the overwhelming number of 86 submissions, which almost doubled the 48 subm- sions received for LION’s second edition in December 2007. As in the ?rst two editions, the submissions to LION 3 could be in three formats: (a) original novel and unpublished work for publication in the post-conference proceedings, (b) extended abstracts of work-in-progressor a position statement, and (c) recently submitted or published journal articles for oral presentations. The 86 subm- sions received include 72, ten, and four articles for categories (a), (b), and (c), respectively.
Algorithms Advances In Research And Application 2012 Edition
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Author :
language : en
Publisher: ScholarlyEditions
Release Date : 2012-12-26
Algorithms Advances In Research And Application 2012 Edition written by and has been published by ScholarlyEditions this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-26 with Computers categories.
Algorithms—Advances in Research and Application: 2012 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Algorithms. The editors have built Algorithms—Advances in Research and Application: 2012 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Algorithms in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Algorithms—Advances in Research and Application: 2012 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.
Reinforcement Learning Algorithms Analysis And Applications
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Author : Boris Belousov
language : en
Publisher: Springer Nature
Release Date : 2021-01-02
Reinforcement Learning Algorithms Analysis And Applications written by Boris Belousov and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-02 with Technology & Engineering categories.
This book reviews research developments in diverse areas of reinforcement learning such as model-free actor-critic methods, model-based learning and control, information geometry of policy searches, reward design, and exploration in biology and the behavioral sciences. Special emphasis is placed on advanced ideas, algorithms, methods, and applications. The contributed papers gathered here grew out of a lecture course on reinforcement learning held by Prof. Jan Peters in the winter semester 2018/2019 at Technische Universität Darmstadt. The book is intended for reinforcement learning students and researchers with a firm grasp of linear algebra, statistics, and optimization. Nevertheless, all key concepts are introduced in each chapter, making the content self-contained and accessible to a broader audience.
Automated Design Of Machine Learning And Search Algorithms
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Author : Nelishia Pillay
language : en
Publisher: Springer Nature
Release Date : 2021-07-28
Automated Design Of Machine Learning And Search Algorithms written by Nelishia Pillay and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-28 with Computers categories.
This book presents recent advances in automated machine learning (AutoML) and automated algorithm design and indicates the future directions in this fast-developing area. Methods have been developed to automate the design of neural networks, heuristics and metaheuristics using techniques such as metaheuristics, statistical techniques, machine learning and hyper-heuristics. The book first defines the field of automated design, distinguishing it from the similar but different topics of automated algorithm configuration and automated algorithm selection. The chapters report on the current state of the art by experts in the field and include reviews of AutoML and automated design of search, theoretical analyses of automated algorithm design, automated design of control software for robot swarms, and overfitting as a benchmark and design tool. Also covered are automated generation of constructive and perturbative low-level heuristics, selection hyper-heuristics for automated design, automated design of deep-learning approaches using hyper-heuristics, genetic programming hyper-heuristics with transfer knowledge and automated design of classification algorithms. The book concludes by examining future research directions of this rapidly evolving field. The information presented here will especially interest researchers and practitioners in the fields of artificial intelligence, computational intelligence, evolutionary computation and optimisation.
Signal Processing And Machine Learning For Biomedical Big Data
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Author : Ervin Sejdic
language : en
Publisher: CRC Press
Release Date : 2018-07-04
Signal Processing And Machine Learning For Biomedical Big Data written by Ervin Sejdic and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-04 with Medical categories.
Within the healthcare domain, big data is defined as any ``high volume, high diversity biological, clinical, environmental, and lifestyle information collected from single individuals to large cohorts, in relation to their health and wellness status, at one or several time points.'' Such data is crucial because within it lies vast amounts of invaluable information that could potentially change a patient's life, opening doors to alternate therapies, drugs, and diagnostic tools. Signal Processing and Machine Learning for Biomedical Big Data thus discusses modalities; the numerous ways in which this data is captured via sensors; and various sample rates and dimensionalities. Capturing, analyzing, storing, and visualizing such massive data has required new shifts in signal processing paradigms and new ways of combining signal processing with machine learning tools. This book covers several of these aspects in two ways: firstly, through theoretical signal processing chapters where tools aimed at big data (be it biomedical or otherwise) are described; and, secondly, through application-driven chapters focusing on existing applications of signal processing and machine learning for big biomedical data. This text aimed at the curious researcher working in the field, as well as undergraduate and graduate students eager to learn how signal processing can help with big data analysis. It is the hope of Drs. Sejdic and Falk that this book will bring together signal processing and machine learning researchers to unlock existing bottlenecks within the healthcare field, thereby improving patient quality-of-life. Provides an overview of recent state-of-the-art signal processing and machine learning algorithms for biomedical big data, including applications in the neuroimaging, cardiac, retinal, genomic, sleep, patient outcome prediction, critical care, and rehabilitation domains. Provides contributed chapters from world leaders in the fields of big data and signal processing, covering topics such as data quality, data compression, statistical and graph signal processing techniques, and deep learning and their applications within the biomedical sphere. This book’s material covers how expert domain knowledge can be used to advance signal processing and machine learning for biomedical big data applications.
Learning And Experiencing Cryptography With Cryptool And Sagemath
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Author : Bernhard Esslinger
language : en
Publisher: Artech House
Release Date : 2023-12-31
Learning And Experiencing Cryptography With Cryptool And Sagemath written by Bernhard Esslinger and has been published by Artech House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-31 with Computers categories.
This book provides a broad overview of cryptography and enables cryptography for trying out. It emphasizes the connections between theory and practice, focuses on RSA for introducing number theory and PKI, and links the theory to the most current recommendations from NIST and BSI. The book also enables readers to directly try out the results with existing tools available as open source. It is different from all existing books because it shows very concretely how to execute many procedures with different tools. The target group could be self-learners, pupils and students, but also developers and users in companies. All code written with these open-source tools is available. The appendix describes in detail how to use these tools. The main chapters are independent from one another. At the end of most chapters, you will find references and web links. The sections have been enriched with many footnotes. Within the footnotes you can see where the described functions can be called and tried within the different CrypTool versions, within SageMath or within OpenSSL.
Compendium On Electromagnetic Analysis From Electrostatics To Photonics Fundamentals And Applications For Physicists And Engineers In 5 Volumes
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Author :
language : en
Publisher: World Scientific
Release Date : 2020-06-15
Compendium On Electromagnetic Analysis From Electrostatics To Photonics Fundamentals And Applications For Physicists And Engineers In 5 Volumes written by and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-15 with Technology & Engineering categories.
The five-volume set may serve as a comprehensive reference on electromagnetic analysis and its applications at all frequencies, from static fields to optics and photonics. The material includes micro- and nanomagnetics, the new generation of electric machines, renewable energy, hybrid vehicles, low-noise motors; antennas and microwave devices, plasmonics, metamaterials, lasers, and more.Written at a level accessible to both graduate students and engineers, Electromagnetic Analysis is a comprehensive reference, covering methods and applications at all frequencies (from statics to optical). Each volume contains pedagogical/tutorial material of high archival value as well as chapters on state-of-the-art developments.