Algorithmic Decision Making With Python Resources

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Algorithmic Decision Making with Python Resources

Author : Raymond Bisdorff
Publisher : Springer Nature
ISBN 13 : 303090928X
Total Pages : 366 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Algorithmic Decision Making with Python Resources by : Raymond Bisdorff

Download or read book Algorithmic Decision Making with Python Resources written by Raymond Bisdorff and published by Springer Nature. This book was released on 2022-03-29 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes Python3 programming resources for implementing decision aiding algorithms in the context of a bipolar-valued outranking approach. These computing resources, made available under the name Digraph3, are useful in the field of Algorithmic Decision Theory and more specifically in outranking-based Multiple-Criteria Decision Aiding (MCDA). The first part of the book presents a set of tutorials introducing the Digraph3 collection of Python3 modules and its main objects, such as bipolar-valued digraphs and outranking digraphs. In eight methodological chapters, the second part illustrates multiple-criteria evaluation models and decision algorithms. These chapters are largely problem-oriented and demonstrate how to edit a new multiple-criteria performance tableau, how to build a best choice recommendation, how to compute the winner of an election and how to make rankings or ratings using incommensurable criteria. The book’s third part presents three real-world decision case studies, while the fourth part addresses more advanced topics, such as computing ordinal correlations between bipolar-valued outranking digraphs, computing kernels in bipolar-valued digraphs, testing for confidence or stability of outranking statements when facing uncertain or solely ordinal criteria significance weights, and tempering plurality tyranny effects in social choice problems. The fifth and last part is more specifically focused on working with undirected graphs, tree graphs and forests. The closing chapter explores comparability, split, interval and permutation graphs. The book is primarily intended for graduate students in management sciences, computational statistics and operations research. The chapters presenting algorithms for ranking multicriteria performance records will be of computational interest for designers of web recommender systems. Similarly, the relative and absolute quantile-rating algorithms, discussed and illustrated in several chapters, will be of practical interest to public and private performance auditors.

Algorithmic Decision Theory

Author : RONEN BRAFMAN
Publisher : Springer Science & Business Media
ISBN 13 : 3642248721
Total Pages : 355 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Algorithmic Decision Theory by : RONEN BRAFMAN

Download or read book Algorithmic Decision Theory written by RONEN BRAFMAN and published by Springer Science & Business Media. This book was released on 2011-10-07 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Conference on Algorithmic Decision Theory, ADT 2011, held in Piscataway, NJ, USA, in October 2011. The 24 revised full papers presented were carefully reviewed and selected from 50 submissions.

Towards Equity in Algorithmic Decision Making

Author : William Cai
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (134 download)

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Book Synopsis Towards Equity in Algorithmic Decision Making by : William Cai

Download or read book Towards Equity in Algorithmic Decision Making written by William Cai and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, many high-stakes societal decision-making systems have begun incorporating data and algorithms. This trend raises the question of how decision makers can do so in a way which creates equitable systems which ameliorate inequities. This dissertation considers two broad paths forward towards this goal. First, we review a series of interventions at various stages of the model-building and deployment process. Specifically, we consider how a model-builder might selectively acquire additional information, adaptively sample training data, and add personalization. We show that these interventions allow for model-builders to efficiently allocate resources to create decision-making systems which are inclusive of individuals from vulnerable groups. Second, we review two pieces of work where modern, online data sources give insights which can inform improvements for existing systems. In particular, we first consider how telematics data, containing records on the true prevalence of speeding, sheds light on inequities in traffic enforcement. Then, we see how online game records provide valuable insight into how users make decisions within social networks. Findings from both studies can be incorporated in future design of or interventions in decision-making systems within both spaces. Overall, this dissertation demonstrates two concrete paths for moving towards equitable decision making: intervening to efficiently improve outcomes for underserved groups, and leveraging insights from modern data sources to improve societal decision making systems.

Algorithmic Decision Theory

Author : Patrice Perny
Publisher : Springer
ISBN 13 : 364241575X
Total Pages : 442 pages
Book Rating : 4.6/5 (424 download)

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Book Synopsis Algorithmic Decision Theory by : Patrice Perny

Download or read book Algorithmic Decision Theory written by Patrice Perny and published by Springer. This book was released on 2013-10-28 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed conference proceedings of the Third International Conference on Algorithmic Decision Theory, ADT 2013, held in November 2013 in Bruxelles, Belgium. The 33 revised full papers presented were carefully selected from more than 70 submissions, covering preferences in reasoning and decision making, uncertainty and robustness in decision making, multi-criteria decision analysis and optimization, collective decision making, learning and knowledge extraction for decision support.

Algorithms for Decision Making

Author : Mykel J. Kochenderfer
Publisher : MIT Press
ISBN 13 : 0262047012
Total Pages : 701 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Algorithms for Decision Making by : Mykel J. Kochenderfer

Download or read book Algorithms for Decision Making written by Mykel J. Kochenderfer and published by MIT Press. This book was released on 2022-08-16 with total page 701 pages. Available in PDF, EPUB and Kindle. Book excerpt: A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them. Automated decision-making systems or decision-support systems—used in applications that range from aircraft collision avoidance to breast cancer screening—must be designed to account for various sources of uncertainty while carefully balancing multiple objectives. This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them. The book first addresses the problem of reasoning about uncertainty and objectives in simple decisions at a single point in time, and then turns to sequential decision problems in stochastic environments where the outcomes of our actions are uncertain. It goes on to address model uncertainty, when we do not start with a known model and must learn how to act through interaction with the environment; state uncertainty, in which we do not know the current state of the environment due to imperfect perceptual information; and decision contexts involving multiple agents. The book focuses primarily on planning and reinforcement learning, although some of the techniques presented draw on elements of supervised learning and optimization. Algorithms are implemented in the Julia programming language. Figures, examples, and exercises convey the intuition behind the various approaches presented.

Decision Support System for Mobile Phone Selection Utilizing Fuzzy Hypersoft Sets and Machine Learning

Author : Muhammad Tahir Hamid
Publisher : Infinite Study
ISBN 13 :
Total Pages : 13 pages
Book Rating : 4./5 ( download)

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Book Synopsis Decision Support System for Mobile Phone Selection Utilizing Fuzzy Hypersoft Sets and Machine Learning by : Muhammad Tahir Hamid

Download or read book Decision Support System for Mobile Phone Selection Utilizing Fuzzy Hypersoft Sets and Machine Learning written by Muhammad Tahir Hamid and published by Infinite Study. This book was released on 2024-01-01 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the dynamic landscape of mobile technology, where a myriad of options burgeons, compounded by fluctuating features, diverse price points, and a plethora of specifications, the task of selecting the optimum mobile phone becomes formidable for consumers. This complexity is further exacerbated by the intrinsic ambiguity and uncertainty characterizing consumer preferences. Addressed herein is the deployment of fuzzy hypersoft sets (FHSS) in conjunction with machine learning techniques to forge a decision support system (DSS) that refines the mobile phone selection process. The proposed framework harnesses the synergy between FHSS and machine learning to navigate the multifaceted nature of consumer choices and the attributes of the available alternatives, thereby offering a structured approach aimed at maximizing consumer satisfaction while accommodating various determinants. The integration of FHSS is pivotal in managing the inherent ambiguity and uncertainty of consumer preferences, providing a comprehensive decision-making apparatus amidst a plethora of choices. The elucidation of this study encompasses an easy-to-navigate framework, buttressed by sophisticated Python codes and algorithms, to ameliorate the selection process. This methodology engenders a personalized and engaging avenue for mobile phone selection in an ever-evolving technological epoch. The fidelity to professional terminologies and their consistent application throughout this discourse, as well as in subsequent sections of the study, underscores the meticulous approach adopted to ensure clarity and precision. This study contributes to the extant literature by offering a novel framework that melds the principles of fuzzy set (FS) theory with advanced computational techniques, thereby facilitating a nuanced decision-making process in the realm of mobile phone selection.

Multiple Criteria Decision Aid

Author : Jason Papathanasiou
Publisher : Springer
ISBN 13 : 3319916483
Total Pages : 182 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Multiple Criteria Decision Aid by : Jason Papathanasiou

Download or read book Multiple Criteria Decision Aid written by Jason Papathanasiou and published by Springer. This book was released on 2018-09-19 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple criteria decision aid (MCDA) methods are illustrated in this book through theoretical and computational techniques utilizing Python. Existing methods are presented in detail with a step by step learning approach. Theoretical background is given for TOPSIS, VIKOR, PROMETHEE, SIR, AHP, goal programming, and their variations. Comprehensive numerical examples are also discussed for each method in conjunction with easy to follow Python code. Extensions to multiple criteria decision making algorithms such as fuzzy number theory and group decision making are introduced and implemented through Python as well. Readers will learn how to implement and use each method based on the problem, the available data, the stakeholders involved, and the various requirements needed. Focusing on the practical aspects of the multiple criteria decision making methodologies, this book is designed for researchers, practitioners and advanced graduate students in the applied mathematics, information systems, operations research and business administration disciplines, as well as other engineers and scientists oriented in interdisciplinary research. Readers will greatly benefit from this book by learning and applying various MCDM/A methods. (Adiel Teixeira de Almeida, CDSID-Center for Decision System and Information Development, Universidade Federal de Pernambuco, Recife, Brazil) Promoting the development and application of multicriteria decision aid is essential to ensure more ethical and sustainable decisions. This book is a great contribution to this objective. It is a perfect blend of theory and practice, providing potential users and researchers with the theoretical bases of some of the best-known methods as well as with the computing tools needed to practice, to compare and to put these methods to use. (Jean-Pierre Brans, Vrije Universiteit Brussel, Brussels, Belgium) This book is intended for researchers, practitioners and students alike in decision support who wish to familiarize themselves quickly and efficiently with multicriteria decision aiding algorithms. The proposed approach is original, as it presents a selection of methods from the theory to the practical implementation in Python, including a detailed example. This will certainly facilitate the learning of these techniques, and contribute to their effective dissemination in applications. (Patrick Meyer, IMT Atlantique, Lab-STICC, Univ. Bretagne Loire, Brest, France)

Algorithms and Data Structures with Python

Author : Cuantum Technologies LLC
Publisher : Packt Publishing Ltd
ISBN 13 : 1836208545
Total Pages : 488 pages
Book Rating : 4.8/5 (362 download)

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Book Synopsis Algorithms and Data Structures with Python by : Cuantum Technologies LLC

Download or read book Algorithms and Data Structures with Python written by Cuantum Technologies LLC and published by Packt Publishing Ltd. This book was released on 2024-06-12 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master Python and elevate your algorithmic skills with this comprehensive course. From introductory concepts to advanced computational problems, learn how to efficiently solve complex challenges and optimize your code. Key Features Comprehensive introduction to Python programming and algorithms Detailed exploration of data structures and sorting/searching techniques Advanced topics including graph algorithms and computational problem-solving Book DescriptionBegin your journey with an introduction to Python and algorithms, laying the groundwork for more complex topics. You will start with the basics of Python programming, ensuring a solid foundation before diving into more advanced and sophisticated concepts. As you progress, you'll explore elementary data containers, gaining an understanding of their role in algorithm development. Midway through the course, you’ll delve into the art of sorting and searching, mastering techniques that are crucial for efficient data handling. You will then venture into hierarchical data structures, such as trees and graphs, which are essential for understanding complex data relationships. By mastering algorithmic techniques, you’ll learn how to implement solutions for a variety of computational challenges. The latter part of the course focuses on advanced topics, including network algorithms, string and pattern deciphering, and advanced computational problems. You'll apply your knowledge through practical case studies and optimizations, bridging the gap between theoretical concepts and real-world applications. This comprehensive approach ensures you are well-prepared to handle any programming challenge with confidence.What you will learn Master sorting and searching algorithms Implement hierarchical data structures like trees and graphs Apply advanced algorithmic techniques to solve complex problems Optimize code for efficiency and performance Understand and implement advanced graph algorithms Translate theoretical concepts into practical, real-world solutions Who this book is for This course is designed for a diverse group of learners, including technical professionals, software developers, computer science students, and data enthusiasts. It caters to individuals who have a basic understanding of programming and are eager to deepen their knowledge of Python and algorithms. Whether you're a recent graduate, or an experienced developer looking to expand your skill set, this course is tailored to meet the needs of all types of audiences. Ideal for those aiming to strengthen their algorithmic thinking and improve their coding efficiency.

Algorithmic Decision Theory

Author : Francesca Rossi
Publisher : Springer Science & Business Media
ISBN 13 : 3642044271
Total Pages : 471 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Algorithmic Decision Theory by : Francesca Rossi

Download or read book Algorithmic Decision Theory written by Francesca Rossi and published by Springer Science & Business Media. This book was released on 2009-10-05 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the papers presented at ADT 2009, the first International Conference on Algorithmic Decision Theory. The conference was held in San Servolo, a small island of the Venice lagoon, during October 20-23, 2009. The program of the conference included oral presentations, posters, invited talks, and tutorials. The conference received 65 submissions of which 39 papers were accepted (9 papers were posters). The topics of these papers range from computational social choice preference modeling, from uncertainty to preference learning, from multi-criteria decision making to game theory.

Algorithmic Decision Theory

Author : Dimitris Fotakis
Publisher : Springer Nature
ISBN 13 : 3030877566
Total Pages : 446 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Algorithmic Decision Theory by : Dimitris Fotakis

Download or read book Algorithmic Decision Theory written by Dimitris Fotakis and published by Springer Nature. This book was released on 2021-10-27 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the conference proceedings of the 7th International Conference on Algorithmic Decision Theory, ADT 2021, held in Toulouse, France, in November 2021. The 27 full papers presented were carefully selected from 58 submissions. The papers focus on algorithmic decision theory broadly defined, seeking to bring together researchers and practitioners coming from diverse areas of computer science, economics and operations research in order to improve the theory and practice of modern decision support.

Multi-Objective Decision Making

Author : Diederik M. Roijers
Publisher : Morgan & Claypool Publishers
ISBN 13 : 1681731827
Total Pages : 174 pages
Book Rating : 4.6/5 (817 download)

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Book Synopsis Multi-Objective Decision Making by : Diederik M. Roijers

Download or read book Multi-Objective Decision Making written by Diederik M. Roijers and published by Morgan & Claypool Publishers. This book was released on 2017-04-20 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many real-world decision problems have multiple objectives. For example, when choosing a medical treatment plan, we want to maximize the efficacy of the treatment, but also minimize the side effects. These objectives typically conflict, e.g., we can often increase the efficacy of the treatment, but at the cost of more severe side effects. In this book, we outline how to deal with multiple objectives in decision-theoretic planning and reinforcement learning algorithms. To illustrate this, we employ the popular problem classes of multi-objective Markov decision processes (MOMDPs) and multi-objective coordination graphs (MO-CoGs). First, we discuss different use cases for multi-objective decision making, and why they often necessitate explicitly multi-objective algorithms. We advocate a utility-based approach to multi-objective decision making, i.e., that what constitutes an optimal solution to a multi-objective decision problem should be derived from the available information about user utility. We show how different assumptions about user utility and what types of policies are allowed lead to different solution concepts, which we outline in a taxonomy of multi-objective decision problems. Second, we show how to create new methods for multi-objective decision making using existing single-objective methods as a basis. Focusing on planning, we describe two ways to creating multi-objective algorithms: in the inner loop approach, the inner workings of a single-objective method are adapted to work with multi-objective solution concepts; in the outer loop approach, a wrapper is created around a single-objective method that solves the multi-objective problem as a series of single-objective problems. After discussing the creation of such methods for the planning setting, we discuss how these approaches apply to the learning setting. Next, we discuss three promising application domains for multi-objective decision making algorithms: energy, health, and infrastructure and transportation. Finally, we conclude by outlining important open problems and promising future directions.

Fair and Unbiased Algorithmic Decision Making

Author : Songül Tolan
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (115 download)

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Book Synopsis Fair and Unbiased Algorithmic Decision Making by : Songül Tolan

Download or read book Fair and Unbiased Algorithmic Decision Making written by Songül Tolan and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning algorithms are now frequently used in sensitive contexts that substantially affect the course of human lives, such as credit lending or criminal justice. This is driven by the idea that 'objective' machines base their decisions solely on facts and remain unaffected by human cognitive biases, discriminatory tendencies or emotions. Yet, there is overwhelming evidence showing that algorithms can inherit or even perpetuate human biases in their decision making when they are based on data that contains biased human decisions. This has led to a call for fairness-aware machine learning. However, fairness is a complex concept which is also reflected in the attempts to formalize fairness for algorithmic decision making. Statistical formalizations of fairness lead to a long list of criteria that are each flawed (or harmful even) in different contexts. Moreover, inherent tradeoffs in these criteria make it impossible to unify them in one general framework. Thus, fairness constraints in algorithms have to be specific to the domains to which the algorithms are applied. In the future, research in algorithmic decision making systems should be aware of data and developer biases and add a focus on transparency to facilitate regular fairness audits.

Applied Computational Thinking with Python

Author : Sofía De Jesús
Publisher : Packt Publishing Ltd
ISBN 13 : 183921676X
Total Pages : 420 pages
Book Rating : 4.8/5 (392 download)

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Book Synopsis Applied Computational Thinking with Python by : Sofía De Jesús

Download or read book Applied Computational Thinking with Python written by Sofía De Jesús and published by Packt Publishing Ltd. This book was released on 2020-11-27 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use the computational thinking philosophy to solve complex problems by designing appropriate algorithms to produce optimal results across various domains Key FeaturesDevelop logical reasoning and problem-solving skills that will help you tackle complex problemsExplore core computer science concepts and important computational thinking elements using practical examplesFind out how to identify the best-suited algorithmic solution for your problemBook Description Computational thinking helps you to develop logical processing and algorithmic thinking while solving real-world problems across a wide range of domains. It's an essential skill that you should possess to keep ahead of the curve in this modern era of information technology. Developers can apply their knowledge of computational thinking to solve problems in multiple areas, including economics, mathematics, and artificial intelligence. This book begins by helping you get to grips with decomposition, pattern recognition, pattern generalization and abstraction, and algorithm design, along with teaching you how to apply these elements practically while designing solutions for challenging problems. You’ll then learn about various techniques involved in problem analysis, logical reasoning, algorithm design, clusters and classification, data analysis, and modeling, and understand how computational thinking elements can be used together with these aspects to design solutions. Toward the end, you will discover how to identify pitfalls in the solution design process and how to choose the right functionalities to create the best possible algorithmic solutions. By the end of this algorithm book, you will have gained the confidence to successfully apply computational thinking techniques to software development. What you will learnFind out how to use decomposition to solve problems through visual representationEmploy pattern generalization and abstraction to design solutionsBuild analytical skills required to assess algorithmic solutionsUse computational thinking with Python for statistical analysisUnderstand the input and output needs for designing algorithmic solutionsUse computational thinking to solve data processing problemsIdentify errors in logical processing to refine your solution designApply computational thinking in various domains, such as cryptography, economics, and machine learningWho this book is for This book is for students, developers, and professionals looking to develop problem-solving skills and tactics involved in writing or debugging software programs and applications. Familiarity with Python programming is required.

Decision Making Applications in Modern Power Systems

Author : Shady H.E. Abdel Aleem
Publisher : Academic Press
ISBN 13 : 0128166266
Total Pages : 576 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Decision Making Applications in Modern Power Systems by : Shady H.E. Abdel Aleem

Download or read book Decision Making Applications in Modern Power Systems written by Shady H.E. Abdel Aleem and published by Academic Press. This book was released on 2019-09-21 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision Making Applications in Modern Power Systems presents an enhanced decision-making framework for power systems. Designed as an introduction to enhanced electricity system analysis using decision-making tools, it provides an overview of the different elements, levels and actors involved within an integrated framework for decision-making in the power sector. In addition, it presents a state-of-play on current energy systems, strategies, alternatives, viewpoints and priorities in support of decision-making in the electric power sector, including discussions of energy storage and smart grids. As a practical training guide on theoretical developments and the application of advanced methods for practical electrical energy engineering problems, this reference is ideal for use in establishing medium-term and long-term strategic plans for the electric power and energy sectors. Provides panoramic coverage of state-of-the-art energy systems, strategies and priorities in support of electrical power decision-making Introduces innovative research outcomes, programs, algorithms and approaches to address challenges in understanding, creating and managing complex techno-socio-economic engineering systems Includes practical training on theoretical developments and the application of advanced methods for realistic electrical energy engineering problems

Mastering Algorithm in Python

Author : Ed Norex a
Publisher : Independently Published
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.8/5 (835 download)

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Book Synopsis Mastering Algorithm in Python by : Ed Norex a

Download or read book Mastering Algorithm in Python written by Ed Norex a and published by Independently Published. This book was released on 2024-03-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the art of solving complex problems with "Mastering Algorithm in Python," your comprehensive guide to understanding and applying algorithms using one of the most versatile programming languages. Whether you're a beginner eager to dive into the world of computer science or a seasoned professional looking to sharpen your skills, this book covers everything from fundamental concepts to advanced techniques. Unlock the secrets of data structures, delve into the intricacies of searching and sorting algorithms, navigate through the complexities of graph algorithms, and conquer challenges with dynamic programming, greedy algorithms, divide and conquer strategies, and backtracking algorithms. Elevate your expertise further as you explore advanced topics including machine learning and graphical models, all illustrated through clear, practical Python examples. With its carefully structured chapters, detailed explanations, and hands-on code examples, "Mastering Algorithm in Python" serves as both a thorough learning resource and a valuable reference tool. Whether you're aiming to enhance your algorithmic thinking, tackle real-world data problems, or simply broaden your programming knowledge, this book will empower you to achieve your goals. Prepare to embark on a journey that will sharpen your problem-solving skills and transform the way you approach challenges in the realm of computer science.

Python Algorithms

Author : Magnus Lie Hetland
Publisher : Apress
ISBN 13 : 1430232382
Total Pages : 325 pages
Book Rating : 4.4/5 (32 download)

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Book Synopsis Python Algorithms by : Magnus Lie Hetland

Download or read book Python Algorithms written by Magnus Lie Hetland and published by Apress. This book was released on 2011-02-27 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python Algorithms explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science, but in a highly pedagogic and readable manner. The book covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others himself.

Ethics, Machine Learning, and Python in Geospatial Analysis

Author : Galety, Mohammad Gouse
Publisher : IGI Global
ISBN 13 :
Total Pages : 359 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Ethics, Machine Learning, and Python in Geospatial Analysis by : Galety, Mohammad Gouse

Download or read book Ethics, Machine Learning, and Python in Geospatial Analysis written by Galety, Mohammad Gouse and published by IGI Global. This book was released on 2024-04-29 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: In geospatial analysis, navigating the complexities of data interpretation and analysis presents a formidable challenge. Traditional methods often need to efficiently handle vast volumes of geospatial data while providing insightful and actionable results. Scholars and practitioners grapple with manual or rule-based approaches, hindering progress in understanding and addressing pressing issues such as climate change, urbanization, and resource management. Ethics, Machine Learning, and Python in Geospatial Analysis offers a solution to the challenges faced by leveraging the extensive library support and user-friendly interface of Python and machine learning. The book’s meticulously crafted chapters guide readers through the intricacies of Python programming and its application in geospatial analysis, from fundamental concepts to advanced techniques.