Books [Ben Klemens] Modeling with Data: Tools and Techniques for Scientific Computing
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Modeling with Data fully explains how to execute computationally intensive analyses on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, how to create and debug statistical models, and how to run an analysis and evaluate the results.
Ben Klemens introduces a set of open and unlimited tools, and uses them to demonstrate data management, analysis, and simulation techniques essential for dealing with large data sets and computationally intensive procedures. He then demonstrates how to easily apply these tools to the many threads of statistical technique, including...
Books [Philipp K. Janert] Feedback Control for Computer Systems: Introducing Control Theory to Enterprise Programmers
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How can you take advantage of feedback control for enterprise programming? With this book, author Philipp K. Janert demonstrates how the same principles that govern cruise control in your car also apply to data center management and other enterprise systems. Through case studies and hands-on simulations, you’ll learn methods to solve several control issues, including mechanisms to spin up more servers automatically when web traffic spikes.
Feedback is ideal for controlling large, complex systems, but its use in software engineering raises unique issues. This book provides basic theory and lots of practical advice for programmers...
Books [Howard Corb] Interest Rate Swaps And Other Derivatives
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The first swap was executed over thirty years ago. Since then, the interest rate swaps and other derivative markets have grown and diversified in phenomenal directions. Derivatives are used today by a myriad of institutional investors for the purposes of risk management, expressing a view on the market, and pursuing market opportunities that are otherwise unavailable using more traditional financial instruments. In this volume, Howard Corb explores the concepts behind interest rate swaps and the many derivatives that evolved from them.
Corb's book uniquely marries academic rigor and real-world trading experience in a compelling...
Books [Ruth Curtain, Hans Zwart] Introduction to Infinite-Dimensional Systems Theory: A State-Space Approach
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Infinite-dimensional systems is a well established area of research with an ever increasing number of applications. Given this trend, there is a need for an introductory text treating system and control theory for this class of systems in detail. This textbook is suitable for courses focusing on the various aspects of infinite-dimensional state space theory. This book is made accessible for mathematicians and post-graduate engineers with a minimal background in infinite-dimensional system theory. To this end, all the system theoretic concepts introduced throughout the text are illustrated by the same types of examples, namely...
Books [Constantin Milici, Gheorghe Drăgănescu, J. Tenreiro Machado] Introduction to Fractional Differential Equations
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This book introduces a series of problems and methods insufficiently discussed in the field of Fractional Calculus – a major, emerging tool relevant to all areas of scientific inquiry. The authors present examples based on symbolic computation, written in Maple and Mathematica, and address both mathematical and computational areas in the context of mathematical modeling and the generalization of classical integer-order methods. Distinct from most books, the present volume fills the gap between mathematics and computer fields, and the transition from integer- to fractional-order methods.
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Books [Sal Rodriguez] Applied Computational Fluid Dynamics and Turbulence Modeling: Practical Tools, Tips and Techniques
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This unique text provides engineering students and practicing professionals with a comprehensive set of practical, hands-on guidelines and dozens of step-by-step examples for performing state-of-the-art, reliable computational fluid dynamics (CFD) and turbulence modeling. Key CFD and turbulence programs are included as well. The text first reviews basic CFD theory, and then details advanced applied theories for estimating turbulence, including new algorithms created by the author. The book gives practical advice on selecting appropriate turbulence models and presents best CFD practices for modeling and generating reliable...
Books [David Bohm] Quantum Theory
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This superb text by David Bohm, formerly Princeton University and Emeritus Professor of Theoretical Physics at Birkbeck College, University of London, provides a formulation of the quantum theory in terms of qualitative and imaginative concepts that have evolved outside and beyond classical theory. Although it presents the main ideas of quantum theory essentially in nonmathematical terms, it follows these with a broad range of specific applications that are worked out in considerable mathematical detail.
Addressed primarily to advanced undergraduate students, the text begins with a study of the physical formulation of the quantum...
Books [Dan A Simovici] Mathematical Analysis For Machine Learning And Data Mining
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This compendium provides a self-contained introduction to mathematical analysis in the field of machine learning and data mining. The mathematical analysis component of the typical mathematical curriculum for computer science students omits these very important ideas and techniques which are indispensable for approaching specialized area of machine learning centered around optimization such as support vector machines, neural networks, various types of regression, feature selection, and clustering. The book is of special interest to researchers and graduate students who will benefit from these application areas discussed in the book...
Books [Anthony L. L. Caterini, Dong Eui Chang] Deep Neural Networks In A Mathematical Framework
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This SpringerBrief describes how to build a rigorous end-to-end mathematical framework for deep neural networks. The authors provide tools to represent and describe neural networks, casting previous results in the field in a more natural light. In particular, the authors derive gradient descent algorithms in a unified way for several neural network structures, including multilayer perceptrons, convolutional neural networks, deep autoencoders and recurrent neural networks. Furthermore, the authors developed framework is both more concise and mathematically intuitive than previous representations of neural networks.
This SpringerBrief...
Books [Mark H. Holmes] Introduction to the Foundations of Applied Mathematics
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FOAM. This acronym has been used for over ?fty years at Rensselaer to designate an upper-division course entitled, Foundations of Applied Ma- ematics. This course was started by George Handelman in 1956, when he came to Rensselaer from the Carnegie Institute of Technology. His objective was to closely integrate mathematical and physical reasoning, and in the p- cess enable students to obtain a qualitative understanding of the world we live in. FOAM was soon taken over by a young faculty member, Lee Segel. About this time a similar course, Introduction to Applied Mathematics, was introduced by Chia-Ch’iao Lin at the Massachusetts...
Books [Konnor Cluster] Python Machine Learning: A Step-by-Step Guide to Scikit-Learn and TensorFlow (Includes a Python Programming Crash Course)
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If you need to learn how to use the Python Programming Language to implement your own Machine Learning solution, and you are searching for a reference to start from, then keep reading.
Machine learning represents now the most interesting, performing and growing technology among all technologies related to Artificial Intelligence and represents also an incredible opportunity if you want to grow your business or if you are searching for a new job, but it’s not very easy to understand how it works. Sometimes, even the most seasoned and skilled engineers are scared to approach this new topic.
This book can assist you in understanding...
Books [Anand Deshpande] Artificial Intelligence For Big Data: Complete Guide To Automating Big Data Solutions Using Artificial Intelligence Techniques
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Key Features
- Implement Artificial Intelligence techniques to build smart applications using Deeplearning4j a Java deep learning library
- Create smart self learning and decision making systems
- Develop smarter Big data applications to get better insights from your analysis
Book Description
In the age of big data, companies have growing amount of consumer data than ever before - far more than human and their current technologies can ever hope to keep up with. Artificial Intelligence closes the gap by moving far past human limitations to consume and analyze data...Books [Shoshana Zuboff] In The Age Of The Smart Machine : The Future Of Work And Power
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Books [Anand J. Kulkarn, Suresh Satapathy] Optimization in Machine Learning and Applications (Algorithms for Intelligent Systems)
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This book discusses one of the major applications of artificial intelligence: the use of machine learning to extract useful information from multimodal data. It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The book also presents formulations of real-world machine learning problems, and discusses AI solution methodologies as standalone or hybrid approaches. Lastly, it proposes novel metaheuristic methods to solve complex machine learning problems. Featuring valuable insights, the book helps readers explore new...
Books [Stephen Muggleton] Inductive Logic Programming (Apic Studies in Data Processing)
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Inductive logic programming is a new research area formed at the intersection of machine learning and logic programming. While the influence of logic programming has encouraged the development of strong theoretical foundations, this new area is inheriting its experimental orientation from machine learning. Inductive Logic Programming will be an invaluable text for all students of computer science, machine learning and logic programming at an advanced level.
* Examination of the background to current developments within the area
* Identification of the various goals and aspirations for the increasing body of researchers in inductive...
Books [Snehashish Chakraverty, Deepti Moyi Sahoo, Nisha Rani Mahato] Concepts Of Soft Computing: Fuzzy And Ann With Programming
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This book discusses soft computing, which provides an efficient platform to deal with imprecision, uncertainty, vagueness and approximation in order to attain robustness and reliable computing. It explores two major concepts of soft computing: fuzzy set theory and neural networks, which relate to uncertainty handling and machine learning techniques respectively. Generally, fuzzy sets are considered as vague or uncertain sets having membership function lying between 0 and 1, and ANN is a type of artificial intelligence that attempts to imitate the way a human brain works by configuring specific applications, for instance pattern...
Books [Yoshua Bengio] Learning Deep Architectures For Ai (Foundations and Trends(r) in Machine Learning)
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Can machine learning deliver AI? Theoretical results, inspiration from the brain and cognition, as well as machine learning experiments suggest that in order to learn the kind of complicated functions that can represent high-level abstractions (e.g. in vision, language, and other AI-level tasks), one would need deep architectures. Deep architectures are composed of multiple levels of non-linear operations, such as in neural nets with many hidden layers, graphical models with many levels of latent variables, or in complicated propositional formulae re-using many sub-formulae. Each level of the architecture represents features at a...
Books [Bastien Chopard, Marco Tomassini] An Introduction To Metaheuristics For Optimization (Natural Computing Series))
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The authors stress the relative simplicity, efficiency, flexibility of use, and suitability of various approaches used to solve difficult optimization problems. The authors are experienced, interdisciplinary lecturers and researchers and in their explanations they demonstrate many shared foundational concepts among the key methodologies.
This textbook is a suitable introduction for undergraduate and graduate students, researchers, and professionals in computer science, engineering, and logistics.
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Books [Simon Rogers, Mark Girolami] A First Course in Machine Learning (Chapman & Hall/CRC Machine Learning & Pattern Recognition) 2nd Edition
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"A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations of Bayesian analysis in the simplest of settings, and goes all the way to the frontiers of the subject such as infinite mixture models, GPs, and MCMC."
―Devdatt Dubhashi, Professor, Department of Computer Science and Engineering, Chalmers University, Sweden
"This textbook manages to be easier to read than other comparable books in the subject while retaining all the rigorous treatment needed. The...
Books [Asit Kumar Datta, Madhura Datta, Pradipta Kumar Banerjee] Face Detection and Recognition: Theory and Practice
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Face detection and recognition are the nonintrusive biometrics of choice in many security applications. Examples of their use include border control, driver’s license issuance, law enforcement investigations, and physical access control.
Face Detection and Recognition: Theory and Practice
elaborates on andexplains the theory and practice of face detection and recognition systems currently in vogue. The book begins with an introduction to the state of the art, offering a general review of the available methods and an indication of future research using cognitive neurophysiology. The text then:
- Explores subspace methods for...
Books [Steve Rabin] Mathematical Logic For Computer Science
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Mathematical Logic for Computer Science is a mathematics textbook with theorems and proofs, but the choice of topics has been guided by the needs of students of computer science. The method of semantic tableaux provides an elegant way to teach logic that is both theoretically sound and easy to understand. The uniform use of tableaux-based techniques facilitates learning advanced logical systems based on what the student has learned from elementary systems.
The logical systems presented are: propositional logic, first-order logic, resolution and its application to logic programming, Hoare logic for the verification of sequential...
Books [Steve Rabin] Game AI Pro 3: Collected Wisdom of Game AI Professionals
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Game AI Pro3: Collected Wisdom of Game AI Professionals presents state-of-the-art tips, tricks, and techniques drawn from developers of shipped commercial games as well as some of the best-known academics in the field. This book acts as a toolbox of proven techniques coupled with the newest advances in game AI. These techniques can be applied to almost any game and include topics such as behavior trees, utility theory, path planning, character behavior, and tactical reasoning.
KEY FEATURES
- Contains 42 chapters from 50 of the game industry’s top developers and researchers.
- Provides real-life case studies of game AI in...
Books [Bernard Marr] Artificial Intelligence In Practice: How 50 Successful Companies Used Ai And Machine Learning To Solve Problems
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Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting fifty case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and...
Books [Ralf T. Kreutzer, Marie Sirrenberg] Understanding Artificial Intelligence: Fundamentals, Use Cases And Methods For A Corporate Ai Journey
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What is Artificial Intelligence and how to exploit it?.- Basics and drivers of Artificial Intelligence.- Fields of application of Artificial Intelligence - production area.- Fields of application of Artificial Intelligence - customer service, marketing and sales.- Fields of application of Artificial Intelligence - retail, service and maintenance sector.- Fields of application of Artificial Intelligence - health care, education and human resource management.- Fields of application of Artificial Intelligence - energy sector, smart home, mobility and transport.- Fields of application of Artificial Intelligence - financial services and...
Books [Emmanuel Ameisen] Building Machine Learning Powered Applications: Going from Idea to Product
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Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, you’ll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers―including experienced practitioners and novices alike―will learn the tools, best practices, and challenges involved in building a real-world ML application step by step.
Author Emmanuel Ameisen, an experienced data scientist who led an AI education program, demonstrates practical ML concepts using code snippets, illustrations, screenshots, and...
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