Articles by "Algorithms"

Showing posts with label Algorithms. Show all posts

Joel Grus ... 406 pages - Publisher: O'Reilly Media; 2nd edition (May, 2019) ... Language: English - ISBN-10: 1492041130 - ISBN-13: 978-1492041139.

To really learn data science, you should not only master the tools—data science libraries, frameworks, modules, and toolkits—but also understand the ideas and principles underlying them. Updated for Python 3.6, this second edition of Data Science from Scratch shows you how these tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with the hacking skills you need to get started as a data scientist. Packed with new material on deep learning, statistics, and natural language processing, this updated book shows you how to find the gems in today’s messy glut of data.

Marcos Lopez de Prado ... 400 pages - Publisher: Wiley; (February, 2018) ... Language: English - ASIN: B079KLDW21 by Amazon.

Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.

Kevin Lioy ... 127 pages - Publisher: Independently Published; (November, 2019) ... Language: English - ISBN-10: 1704429161 - ISBN-13: 978-1704429168.

Python Advanced Programming approaches this programming language in a very practical method to make sure you can learn everything you need to start working with Python as soon as possible and to handle advanced feature of this unique language. You will learn: Advanced procedural programming techniques. What is Dynamic Code Execution. Advanced OOP functions most developers are not aware of. Functional-style programming with Python. How to debug, test and profile your software. How to handle multiple processes. The best techniques to spread the workload on different threads.

Sanjiv Jaggia, Alison Kelly ... 587 pages - Publisher: McGraw-Hill Education; 2nd edition (February, 2019) ... Language: English - ISBN-10: 1260547655 - ISBN-13: 978-1260547658.

Essentials of Business Statistics: Communicating with Numbers is a core statistics textbook that sparks student interest and bridges the gap between how statistics is taught and how practitioners think about and apply statistical methods. Throughout the text, the emphasis is on communicating with numbers rather than on number crunching. By incorporating the perspective of professional users, the subject matter is more relevant and the presentation of material more straightforward for students. Connect is the only integrated learning system that empowers students by continuously adapting to deliver precisely what they need, when they need it, and how they need it, so that your class time is more engaging and effective.

Mehmed Kantardzic ... 672 pages - Publisher: Wiley-IEEE Press; 3rd edition (November, 2019) ... Language: English - ISBN-10: 1119516048 - ISBN-13: 978-1119516040.

Presents the latest techniques for analyzing and extracting information from large amounts of data in high-dimensional data spaces: The revised and updated third edition of Data Mining contains in one volume an introduction to a systematic approach to the analysis of large data sets that integrates results from disciplines such as statistics, artificial intelligence, data bases, pattern recognition, and computer visualization. Advances in deep learning technology have opened an entire new spectrum of applications. The author―a noted expert on the topic―explains the basic concepts, models, and methodologies that have been developed in recent years. This new edition introduces and expands on many topics, as well as providing revised sections on software tools and data mining applications. Additional changes include an updated list of references for further study, and an extended list of problems and questions that relate to each chapter.This third edition presents new and expanded information that: • Explores big data and cloud computing • Examines deep learning • Includes information on convolutional neural networks (CNN) • Offers reinforcement learning • Contains semi-supervised learning and S3VM • Reviews model evaluation for unbalanced data. Written for graduate students in computer science, computer engineers, and computer information systems professionals, the updated third edition of Data Mining continues to provide an essential guide to the basic principles of the technology and the most recent developments in the field.

Bruce Ratner ... 724 pages - Publisher: Chapman and Hall/CRC; 3rd edition (June, 2017) ... Language: English - ISBN-10: 9781498797603 - ISBN-13: 978-1498797603. 

Interest in predictive analytics of big data has grown exponentially in the four years since the publication of Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition. In the third edition of this bestseller, the author has completely revised, reorganized, and repositioned the original chapters and produced 13 new chapters of creative and useful machine-learning data mining techniques. In sum, the 43 chapters of simple yet insightful quantitative techniques make this book unique in the field of data mining literature.

What is new in the Third Edition: The current chapters have been completely rewritten. + The core content has been extended with strategies and methods for problems drawn from the top predictive analytics conference and statistical modeling workshops. + Adds thirteen new chapters including coverage of data science and its rise, market share estimation, share of wallet modeling without survey data, latent market segmentation, statistical regression modeling that deals with incomplete data, decile analysis assessment in terms of the predictive power of the data, and a user-friendly version of text mining, not requiring an advanced background in natural language processing (NLP). + Includes SAS subroutines which can be easily converted to other languages. As in the previous edition, this book offers detailed background, discussion, and illustration of specific methods for solving the most commonly experienced problems in predictive modeling and analysis of big data. The author addresses each methodology and assigns its application to a specific type of problem. To better ground readers, the book provides an in-depth discussion of the basic methodologies of predictive modeling and analysis. While this type of overview has been attempted before, this approach offers a truly nitty-gritty, step-by-step method that both tyros and experts in the field can enjoy playing with.

Ying Tan, Yuhui Shi, Qirong Tang ... 820 pages - Publisher: Springer; (June, 2018) ... Language: English - ASIN: B07DMV9N6P by Amazon.

This book constitutes the refereed proceedings of the Third International Conference on Data Mining and Big Data, DMBD 2018, held in Shanghai, China, in June 2018. The 74 papers presented in this volume were carefully reviewed and selected from 126 submissions. They are organized in topical sections named: database, data preprocessing, matrix factorization, data analysis, visualization, visibility analysis, clustering, prediction, classification, pattern discovery, text mining and knowledge management, recommendation system in social media, deep learning, big data, Industry 4.0, practical applications

Galit Shmueli, Kenneth C. Lichtendahl Jr. ... 232 pages - Publisher: Axelrod Schnall Publishers; 2nd edition (July, 2016) ... Language: English - ISBN-10: 0997847913 - ISBN-13: 978-0997847918. 

Practical Time Series Forecasting with R: A Hands-On Guide, 2nd Edition provides an applied approach to time-series forecasting. Forecasting is an essential component of predictive analytics. The book introduces popular forecasting methods and approaches used in a variety of business applications. The book offers clear explanations, practical examples, and end-of-chapter exercises and cases. Readers will learn to use forecasting methods using the free open-source R software to develop effective forecasting solutions that extract business value from time-series data.

Featuring improved organization and new material, the Second Edition also includes: Popular forecasting methods including smoothing algorithms, regression models, and neural networks + A practical approach to evaluating the performance of forecasting solutions + A business-analytics exposition focused on linking time-series forecasting to business goals + Guided cases for integrating the acquired knowledge using real data + End-of-chapter problems to facilitate active learning + A companion site with data sets, R code, learning resources, and instructor materials (solutions to exercises, case studies)Globally-available textbook, available in both softcover and Kindle formats

Practical Time Series Forecasting with R: A Hands-On Guide, Second Edition is the perfect textbook for upper-undergraduate, graduate and MBA-level courses as well as professional programs in data science and business analytics. The book is also designed for practitioners in the fields of operations research, supply chain management, marketing, economics, finance and management.

Krishnanand N. Kaipa, Debasish Ghose ... 248 pages - Publisher: Springer; (January, 2017) ... Language: English - ASIN: B01N7R22Z8 by Amazon.

This book provides a comprehensive account of the glowworm swarm optimization (GSO) algorithm, including details of the underlying ideas, theoretical foundations, algorithm development, various applications, and MATLAB programs for the basic GSO algorithm. It also discusses several research problems at different levels of sophistication that can be attempted by interested researchers. The generality of the GSO algorithm is evident in its application to diverse problems ranging from optimization to robotics. Examples include computation of multiple optima, annual crop planning, cooperative exploration, distributed search, multiple source localization, contaminant boundary mapping, wireless sensor networks, clustering, knapsack, numerical integration, solving fixed point equations, solving systems of nonlinear equations, and engineering design optimization. The book is a valuable resource for researchers as well as graduate and undergraduate students in the area of swarm intelligence and computational intelligence and working on these topics.

Michael Z. Zgurovsky, Yuriy P. Zaychenko ... 304 pages - Publisher: Springer (May, 2020) ... Language: English - ISBN-10: 3030143007 - ISBN-13: 978-3030143008.

The book is devoted to the analysis of big data in order to extract from these data hidden patterns necessary for making decisions about the rational behavior of complex systems with the different nature that generate this data. To solve these problems, a group of new methods and tools is used, based on the self-organization of computational processes, the use of crisp and fuzzy cluster analysis methods, hybrid neural-fuzzy networks, and others. The book solves various practical problems. In particular, for the tasks of 3D image recognition and automatic speech recognition large-scale neural networks with applications for Deep Learning systems were used. Application of hybrid neuro-fuzzy networks for analyzing stock markets was presented. The analysis of big historical, economic and physical data revealed the hidden Fibonacci pattern about the course of systemic world conflicts and their connection with the Kondratieff big economic cycles and the Schwabe–Wolf solar activity cycles. The book is useful for system analysts and practitioners working with complex systems in various spheres of human activity.

Olaf Wolkenhauer  ... 296 pages - Publisher: Wiley-Interscience; (July, 2001) ... Language: English - ISBN-10: 0471416568 - ISBN-13: 978-0471416562.

A survey of the philosophical implications and practical applications of fuzzy systems: Fuzzy mathematical concepts such as fuzzy sets, fuzzy logic, and similarity relations represent one of the most exciting currents in modern engineering and have great potential in applications ranging from control theory to bioinformatics. Data Engineering guides the reader through a number of concepts interconnected by fuzzy mathematics and discusses these concepts from a systems engineering perspective to showcase the continuing vitality, attractiveness, and applicability of fuzzy mathematics.

The author discusses the fundamental aspects of data analysis, systems modeling, and uncertainty calculi. He avoids a narrow discussion of specialized methodologies and takes a holistic view of the nature and application of fuzzy systems, considering principles, paradigms, and methodologies along the way. This broad coverage includes: * Fundamentals of modeling, identification, and clustering * System analysis * Uncertainty techniques * Random-set modeling and identification * Fuzzy inference engines * Fuzzy classification, control, and mathematics. In the important emerging field of bioinformatics, the book sets out how to encode a natural system in mathematical models, describes methods to identify interrelationships and interactions from data, and thereby helps the practitioner to decide which variables to measure and why. Data Engineering serves as an up-to-date and informative survey of the theoretical and practical tools for analyzing complex systems. It offers a unique treatment of complex issues that is accessible to students and researchers from a variety of backgrounds.

Ross Baldick ... 792 pages - Publisher: Cambridge University Press; (January, 2009) ... Language: English - ISBN-10: 0521100283 - ISBN-13: 978-0521100281.

The starting point in the formulation of any numerical problem is to take an intuitive idea about the problem in question and to translate it into precise mathematical language. This book provides step-by-step descriptions of how to formulate numerical problems so that they can be solved by existing software. It examines various types of numerical problems and develops techniques for solving them. A number of engineering case studies are used to illustrate in detail the formulation process. The case studies motivate the development of efficient algorithms that involve, in some cases, transformation of the problem from its initial formulation into a more tractable form.

Rudra Pratap ... 288 pages - Publisher: Oxford Univ. Press; (November, 2009) ... Language: English - ISBN-10: 0199731241 - ISBN-13: 978-0199731244.

MATLAB, a software package for high-performance numerical computation and visualization, is one of the most widely used tools in the engineering field today. Its broad appeal lies in its interactive environment, which features hundreds of built-in functions for technical computation, graphics, and animation. In addition, MATLAB provides easy extensibility with its own high-level programming language. Enhanced by fun and appealing illustrations, Getting Started with MATLAB employs a casual, accessible writing style that shows users how to enjoy using MATLAB.

Features: * Discusses new features and applications, including the new engine of symbolic computation in MATLAB 7.8 (released March 2009) * Provides two sets of self guided tutorials for learning essential features of MATLAB * Includes updated commands, examples, figure, and graphs * Familiarizes users with MATLAB in just a few hours though self-guided lessons * Covers elementary, advanced, and special functions * Supplements any course that uses MATLAB * Works as a stand-alone tutorial and reference.

Ronald E. Miller ... 676 pages - Publisher: Wiley-Interscience; (November, 1999) ... Language: English - ISBN-10: 0471351695 - ISBN-13: 978-0471351696.

A thorough and highly accessible resource for analysts in a broad range of social sciences: Optimization: Foundations and Applications presents a series of approaches to the challenges faced by analysts who must find the best way to accomplish particular objectives, usually with the added complication of constraints on the available choices. Award-winning educator Ronald E. Miller provides detailed coverage of both classical, calculus-based approaches and newer, computer-based iterative methods. Dr. Miller lays a solid foundation for both linear and nonlinear models and quickly moves on to discuss applications, including iterative methods for root-finding and for unconstrained maximization, approaches to the inequality constrained linear programming problem, and the complexities of inequality constrained maximization and minimization in nonlinear problems. Other important features include: More than 200 geometric interpretations of algebraic results, emphasizing the intuitive appeal of mathematics + Classic results mixed with modern numerical methods to aid users of computer programs + Extensive appendices containing mathematical details important for a thorough understanding of the topic. With special emphasis on questions most frequently asked by those encountering this material for the first time, Optimization: Foundations and Applications is an extremely useful resource for professionals in such areas as mathematics, engineering, economics and business, regional science, geography, sociology, political science, management and decision sciences, public policy analysis, and numerous other social sciences.

Steven J. Miller ... 327 pages - Publisher: American Mathematical Society; (December, 2017) ... Language: English - ISBN-10: 1470441144 - ISBN-13: 978-1470441142.

Optimization Theory is an active area of research with numerous applications; many of the books are designed for engineering classes, and thus have an emphasis on problems from such fields. Covering much of the same material, there is less emphasis on coding and detailed applications as the intended audience is more mathematical. There are still several important problems discussed (especially scheduling problems), but there is more emphasis on theory and less on the nuts and bolts of coding. A constant theme of the text is the ``why'' and the ``how'' in the subject. Why are we able to do a calculation efficiently? How should we look at a problem? Extensive effort is made to motivate the mathematics and isolate how one can apply ideas/perspectives to a variety of problems. As many of the key algorithms in the subject require too much time or detail to analyze in a first course (such as the run-time of the Simplex Algorithm), there are numerous comparisons to simpler algorithms which students have either seen or can quickly learn (such as the Euclidean algorithm) to motivate the type of results on run-time savings.

John Wolberg ... 250 pages - Publisher: Springer Berlin Heidelberg; (February, 2006) ... Language: English - ASIN: B000VHULZG by Amazon.

The preferred method of data analysis of quantitative experiments is the method of least squares. Often, however, the full power of the method is overlooked and very few books deal with this subject at the level that it deserves. The purpose of Data Analysis Using the Method of Least Squares is to fill this gap and include the type of information required to help scientists and engineers apply the method to problems in their special fields of interest. In addition, graduate students in science and engineering doing work of experimental nature can benefit from this book. Particularly, both linear and non-linear least squares, the use of experimental error estimates for data weighting, procedures to include prior estimates, methodology for selecting and testing models, prediction analysis, and some non-parametric methods are discussed.

Andreas Müller, Sarah Guido ... 400 pages - Publisher: O'Reilly Media; (October, 2016) ... Language: English - ISBN-10: 1449369413 - ISBN-13: 978-1449369415.

Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.

With this book, you’ll learn: Fundamental concepts and applications of machine learning + Advantages and shortcomings of widely used machine learning algorithms + How to represent data processed by machine learning, including which data aspects to focus on + Advanced methods for model evaluation and parameter tuning + The concept of pipelines for chaining models and encapsulating your workflow + Methods for working with text data, including text-specific processing techniques + Suggestions for improving your machine learning and data science skills.

Wendy L. Martinez, Angel Martinez, Jeffrey Solka ... 536 pages - Publisher: CRC Press; 2nd edition (December, 2010) ... Language: English - ISBN-10: 1439812209 - ISBN-13: 978-1439812204

Since the publication of the bestselling first edition, many advances have been made in exploratory data analysis (EDA). Covering innovative approaches for dimensionality reduction, clustering, and visualization, Exploratory Data Analysis with MATLAB, Second Edition uses numerous examples and applications to show how the methods are used in practice. New to the Second Edition: Discussions of nonnegative matrix factorization, linear discriminant analysis, curvilinear component analysis, independent component analysis, and smoothing splines - An expanded set of methods for estimating the intrinsic dimensionality of a data set - Several clustering methods, including probabilistic latent semantic analysis and spectral-based clustering - Additional visualization methods, such as a rangefinder boxplot, scatterplots with marginal histograms, biplots, and a new method called Andrews’ images -Instructions on a free MATLAB GUI toolbox for EDA... Like its predecessor, this edition continues to focus on using EDA methods, rather than theoretical aspects. The MATLAB codes for the examples, EDA toolboxes, data sets, and color versions of all figures are available for download at

Gowrishankar S., Veena A. ... 464 pages - Publisher: Chapman and Hall/CRC; (November, 2018) ... Language: English - ISBN-10: 0815394373 - ISBN-13: 978-0815394372

Introduction to Python Programming is written for students who are beginners in the field of computer programming. This book presents an intuitive approach to the concepts of Python Programming for students. This book differs from traditional texts not only in its philosophy but also in its overall focus, level of activities, development of topics, and attention to programming details. The contents of the book are chosen with utmost care after analyzing the syllabus for Python course prescribed by various top universities in USA, Europe, and Asia. Since the prerequisite know-how varies significantly from student to student, the book’s overall overture addresses the challenges of teaching and learning of students which is fine-tuned by the authors’ experience with large sections of students. This book uses natural language expressions instead of the traditional shortened words of the programming world. This book has been written with the goal to provide students with a textbook that can be easily understood and to make a connection between what students are learning and how they may apply that knowledge.

Clarisse Dhaenens, Laetitia Jourdan ... 213 pages - Publisher: Wiley-ISTE; (August, 2016) ... Language: English - ASIN: B01KZO6P4U by Amazon

Big Data is a new field, with many technological challenges to be understood in order to use it to its full potential. These challenges arise at all stages of working with Big Data, beginning with data generation and acquisition. The storage and management phase presents two critical challenges: infrastructure, for storage and transportation, and conceptual models. Finally, to extract meaning from Big Data requires complex analysis. Here the authors propose using metaheuristics as a solution to these challenges; they are first able to deal with large size problems and secondly flexible and therefore easily adaptable to different types of data and different contexts. The use of metaheuristics to overcome some of these data mining challenges is introduced and justified in the first part of the book, alongside a specific protocol for the performance evaluation of algorithms. An introduction to metaheuristics follows. The second part of the book details a number of data mining tasks, including clustering, association rules, supervised classification and feature selection, before explaining how metaheuristics can be used to deal with them. This book is designed to be self-contained, so that readers can understand all of the concepts discussed within it, and to provide an overview of recent applications of metaheuristics to knowledge discovery problems in the context of Big Data.

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