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Parallel Programming for Modern High Performance Computing Systems

Parallel Programming for Modern High Performance Computing Systems

In view of the growing presence and popularity of multicore and manycore processors accelerators and coprocessors as well as clusters using such computing devices the development of efficient parallel applications has become a key challenge to be able to exploit the performance of such systems. This book covers the scope of parallel programming for modern high performance computing systems. It first discusses selected and popular state-of-the-art computing devices and systems available today These include multicore CPUs manycore (co)processors such as Intel Xeon Phi accelerators such as GPUs and clusters as well as programming models supported on these platforms. It next introduces parallelization through important programming paradigms such as master-slave geometric Single Program Multiple Data (SPMD) and divide-and-conquer. The practical and useful elements of the most popular and important APIs for programming parallel HPC systems are discussed including MPI OpenMP Pthreads CUDA OpenCL and OpenACC. It also demonstrates through selected code listings how selected APIs can be used to implement important programming paradigms. Furthermore it shows how the codes can be compiled and executed in a Linux environment. The book also presents hybrid codes that integrate selected APIs for potentially multi-level parallelization and utilization of heterogeneous resources and it shows how to use modern elements of these APIs. Selected optimization techniques are also included such as overlapping communication and computations implemented using various APIs. Features:Discusses the popular and currently available computing devices and cluster systemsIncludes typical paradigms used in parallel programsExplores popular APIs for programming parallel applicationsProvides code templates that can be used for implementation of paradigmsProvides hybrid code examples allowing multi-level parallelizationCovers the optimization of parallel programs

GBP 44.99
1

High Performance Computing Programming and Applications

High Performance Computing Programming and Applications

High Performance Computing: Programming and Applications presents techniques that address new performance issues in the programming of high performance computing (HPC) applications. Omitting tedious details the book discusses hardware architecture concepts and programming techniques that are the most pertinent to application developers for achieving high performance. Even though the text concentrates on C and Fortran the techniques described can be applied to other languages such as C++ and Java. Drawing on their experience with chips from AMD and systems interconnects and software from Cray Inc. the authors explore the problems that create bottlenecks in attaining good performance. They cover techniques that pertain to each of the three levels of parallelism: Message passing between the nodes Shared memory parallelism on the nodes or the multiple instruction multiple data (MIMD) units on the accelerator Vectorization on the inner level After discussing architectural and software challenges the book outlines a strategy for porting and optimizing an existing application to a large massively parallel processor (MPP) system. With a look toward the future it also introduces the use of general purpose graphics processing units (GPGPUs) for carrying out HPC computations. A companion website at www. hybridmulticoreoptimization. com contains all the examples from the book along with updated timing results on the latest released processors. | High Performance Computing Programming and Applications

GBP 59.99
1

Introduction to High-Dimensional Statistics

Introduction to High-Dimensional Statistics

Praise for the first edition: [This book] succeeds singularly at providing a structured introduction to this active field of research. … it is arguably the most accessible overview yet published of the mathematical ideas and principles that one needs to master to enter the field of high-dimensional statistics. … recommended to anyone interested in the main results of current research in high-dimensional statistics as well as anyone interested in acquiring the core mathematical skills to enter this area of research. —Journal of the American Statistical Association Introduction to High-Dimensional Statistics Second Edition preserves the philosophy of the first edition: to be a concise guide for students and researchers discovering the area and interested in the mathematics involved. The main concepts and ideas are presented in simple settings avoiding thereby unessential technicalities. High-dimensional statistics is a fast-evolving field and much progress has been made on a large variety of topics providing new insights and methods. Offering a succinct presentation of the mathematical foundations of high-dimensional statistics this new edition: Offers revised chapters from the previous edition with the inclusion of many additional materials on some important topics including compress sensing estimation with convex constraints the slope estimator simultaneously low-rank and row-sparse linear regression or aggregation of a continuous set of estimators. Introduces three new chapters on iterative algorithms clustering and minimax lower bounds. Provides enhanced appendices minimax lower-bounds mainly with the addition of the Davis-Kahan perturbation bound and of two simple versions of the Hanson-Wright concentration inequality. Covers cutting-edge statistical methods including model selection sparsity and the Lasso iterative hard thresholding aggregation support vector machines and learning theory. Provides detailed exercises at the end of every chapter with collaborative solutions on a wiki site. Illustrates concepts with simple but clear practical examples.

GBP 74.99
1

Producing High-Quality Figures Using SAS/GRAPH and ODS Graphics Procedures

Producing High-Quality Figures Using SAS/GRAPH and ODS Graphics Procedures

Create Top-Quality Figures Using SAS Producing High-Quality Figures Using SAS/GRAPH and ODS Graphics Procedures gives statisticians and SAS programmers practical guidance on presenting research data in high-quality figures that meet the publication requirements of academic institutions and various industries such as pharmaceutical companies agricultural businesses and financial organizations. Choose the Proper Graph Formats Options and Fonts The book provides all the details on selecting the right figure formats options and fonts to produce high-quality figures. In-depth instructions and SAS programs using procedures in both SAS/GRAPH and ODS Graphics show how to generate sample figures in listing graphics formats and ODS document files. Each chapter includes practical examples and SAS programs. Readers can easily modify the SAS programs to develop high-quality figures to meet their own needs. For those unfamiliar with SAS programming and SAS Graphics the author describes how to produce sample figures in SAS ODS Graphics designer a convenient tool for generating figures without having to write SAS programs. The book also discusses how to produce figures in a SAS Enterprise Guide project. | Producing High-Quality Figures Using SAS/GRAPH® and ODS Graphics Procedures

GBP 160.00
1

Numerical Methods for Unsteady Compressible Flow Problems

Numerical Methods for Unsteady Compressible Flow Problems

Numerical Methods for Unsteady Compressible Flow Problems is written to give both mathematicians and engineers an overview of the state of the art in the field as well as of new developments. The focus is on methods for the compressible Navier-Stokes equations the solutions of which can exhibit shocks boundary layers and turbulence. The idea of the text is to explain the important ideas to the reader while giving enough detail and pointers to literature to facilitate implementation of methods and application of concepts. The book covers high order methods in space such as Discontinuous Galerkin methods and high order methods in time in particular implicit ones. A large part of the text is reserved to discuss iterative methods for the arising large nonlinear and linear equation systems. Ample space is given to both state-of-the-art multigrid and preconditioned Newton-Krylov schemes. Features Applications to aerospace high-speed vehicles heat transfer and more besides Suitable as a textbook for graduate-level courses in CFD or as a reference for practitioners in the field

GBP 44.99
1

C++ for Financial Mathematics

C++ for Financial Mathematics

If you know a little bit about financial mathematics but don’t yet know a lot about programming then C++ for Financial Mathematics is for you. C++ is an essential skill for many jobs in quantitative finance but learning it can be a daunting prospect. This book gathers together everything you need to know to price derivatives in C++ without unnecessary complexities or technicalities. It leads the reader step-by-step from programming novice to writing a sophisticated and flexible financial mathematics library. At every step each new idea is motivated and illustrated with concrete financial examples. As employers understand there is more to programming than knowing a computer language. As well as covering the core language features of C++ this book teaches the skills needed to write truly high quality software. These include topics such as unit tests debugging design patterns and data structures. The book teaches everything you need to know to solve realistic financial problems in C++. It can be used for self-study or as a textbook for an advanced undergraduate or master’s level course.

GBP 44.99
1

Numerical Methods for Finance

Numerical Methods for Finance

Featuring international contributors from both industry and academia Numerical Methods for Finance explores new and relevant numerical methods for the solution of practical problems in finance. It is one of the few books entirely devoted to numerical methods as applied to the financial field. Presenting state-of-the-art methods in this area the book first discusses the coherent risk measures theory and how it applies to practical risk management. It then proposes a new method for pricing high-dimensional American options followed by a description of the negative inter-risk diversification effects between credit and market risk. After evaluating counterparty risk for interest rate payoffs the text considers strategies and issues concerning defined contribution pension plans and participating life insurance contracts. It also develops a computationally efficient swaption pricing technology extracts the underlying asset price distribution implied by option prices and proposes a hybrid GARCH model as well as a new affine point process framework. In addition the book examines performance-dependent options variance reduction Value at Risk (VaR) the differential evolution optimizer and put-call-futures parity arbitrage opportunities. Sponsored by DEPFA Bank IDA Ireland and Pioneer Investments this concise and well-illustrated book equips practitioners with the necessary information to make important financial decisions.

GBP 59.99
1

Analyzing High-Dimensional Gene Expression and DNA Methylation Data with R

Analyzing High-Dimensional Gene Expression and DNA Methylation Data with R

Analyzing high-dimensional gene expression and DNA methylation data with R is the first practical book that shows a ``pipeline of analytical methods with concrete examples starting from raw gene expression and DNA methylation data at the genome scale. Methods on quality control data pre-processing data mining and further assessments are presented in the book and R programs based on simulated data and real data are included. Codes with example data are all reproducible. Features: · Provides a sequence of analytical tools for genome-scale gene expression data and DNA methylation data starting from quality control and pre-processing of raw genome-scale data. · Organized by a parallel presentation with explanation on statistical methods and corresponding R packages/functions in quality control pre-processing and data analyses (e. g. clustering and networks). · Includes source codes with simulated and real data to reproduce the results. Readers are expected to gain the ability to independently analyze genome-scaled expression and methylation data and detect potential biomarkers. This book is ideal for students majoring in statistics biostatistics and bioinformatics and researchers with an interest in high dimensional genetic and epigenetic studies.

GBP 66.99
1

Python for Beginners

Python for Beginners

Python is an amazing programming language. It can be applied to almost any programming task. It allows for rapid development and debugging. Getting started with Python is like learning any new skill: it’s important to find a resource you connect with to guide your learning. Luckily there’s no shortage of excellent books that can help you learn both the basic concepts of programming and the specifics of programming in Python. With the abundance of resources it can be difficult to identify which book would be best for your situation. Python for Beginners is a concise single point of reference for all material on python. Provides concise need-to-know information on Python types and statements special method names built-in functions and exceptions commonly used standard library modules and other prominent Python tools Offers practical advice for each major area of development with both Python 3. x and Python 2. x Based on the latest research in cognitive science and learning theory Helps the reader learn how to write effective idiomatic Python code by leveraging its best—and possibly most neglected—features This book focuses on enthusiastic research aspirants who work on scripting languages for automating the modules and tools development of web applications handling big data complex calculations workflow creation rapid prototyping and other software development purposes. It also targets graduates postgraduates in computer science information technology academicians practitioners and research scholars.

GBP 120.00
1

Python for Scientific Computing and Artificial Intelligence

Python for Scientific Computing and Artificial Intelligence

Python for Scientific Computing and Artificial Intelligence is split into 3 parts: in Section 1 the reader is introduced to the Python programming language and shown how Python can aid in the understanding of advanced High School Mathematics. In Section 2 the reader is shown how Python can be used to solve real-world problems from a broad range of scientific disciplines. Finally in Section 3 the reader is introduced to neural networks and shown how TensorFlow (written in Python) can be used to solve a large array of problems in Artificial Intelligence (AI). This book was developed from a series of national and international workshops that the author has been delivering for over twenty years. The book is beginner friendly and has a strong practical emphasis on programming and computational modelling. Features: No prior experience of programming is required Online GitHub repository available with codes for readers to practice Covers applications and examples from biology chemistry computer science data science electrical and mechanical engineering economics mathematics physics statistics and binary oscillator computing Full solutions to exercises are available as Jupyter notebooks on the Web Support Material GitHub Repository of Python Files and Notebooks: https://github. com/proflynch/CRC-Press/ Solutions to All Exercises: Section 1: An Introduction to Python: https://drstephenlynch. github. io/webpages/Solutions_Section_1. html Section 2: Python for Scientific Computing: https://drstephenlynch. github. io/webpages/Solutions_Section_2. html Section 3: Artificial Intelligence: https://drstephenlynch. github. io/webpages/Solutions_Section_3. html

GBP 52.99
1

Design of Experiments for Generalized Linear Models

Design of Experiments for Generalized Linear Models

Generalized Linear Models (GLMs) allow many statistical analyses to be extended to important statistical distributions other than the Normal distribution. While numerous books exist on how to analyse data using a GLM little information is available on how to collect the data that are to be analysed in this way. This is the first book focusing specifically on the design of experiments for GLMs. Much of the research literature on this topic is at a high mathematical level and without any information on computation. This book explains the motivation behind various techniques reduces the difficulty of the mathematics or moves it to one side if it cannot be avoided and gives examples of how to write and run computer programs using R. FeaturesThe generalisation of the linear model to GLMsBackground mathematics and the use of constrained optimisation in RCoverage of the theory behind the optimality of a designIndividual chapters on designs for data that have Binomial or Poisson distributionsBayesian experimental designAn online resource contains R programs used in the bookThis book is aimed at readers who have done elementary differentiation and understand minimal matrix algebra and have familiarity with R. It equips professional statisticians to read the research literature. Nonstatisticians will be able to design their own experiments by following the examples and using the programs provided. | Design of Experiments for Generalized Linear Models

GBP 38.99
1

Applications of Regression for Categorical Outcomes Using R

Applications of Regression for Categorical Outcomes Using R

This book covers the main models within the GLM (i. e. logistic Poisson negative binomial ordinal and multinomial). For each model estimations interpretations model fit diagnostics and how to convey results graphically are provided. There is a focus on graphic displays of results as these are a core strength of using R for statistical analysis. Many in the social sciences are transitioning away from using Stata SPSS and SAS to using R and this book uses statistical models which are relevant to the social sciences. Social Science Applications of Regression for Categorical Outcomes Using R will be useful for graduate students in the social sciences who are looking to expand their statistical knowledge and for Quantitative social scientists due to it’s ability to act as a practitioners guide. Key Features: Applied- in the sense that we will provide code that others can easily adapt Flexible- R is basically just a fancy calculator. Our programs will enable users to derive quantities that they can use in their work Timely- many in the social sciences are currently transitioning to R or are learning it now. Our book will be a useful resource Versatile- we will write functions into an R package that can be applied to all of the regression models we will cover in the book Aesthetically pleasing- one advantage of R relative to other software packages is that graphs are fully customizable. We will leverage this feature to yield high-end graphical displays of results Affordability- R is free. R packages are free. There is no need to purchase site licenses or updates.

GBP 59.99
1

Python for Bioinformatics

Python for Bioinformatics

In today's data driven biology programming knowledge is essential in turning ideas into testable hypothesis. Based on the author’s extensive experience Python for Bioinformatics Second Edition helps biologists get to grips with the basics of software development. Requiring no prior knowledge of programming-related concepts the book focuses on the easy-to-use yet powerful Python computer language. This new edition is updated throughout to Python 3 and is designed not just to help scientists master the basics but to do more in less time and in a reproducible way. New developments added in this edition include NoSQL databases the Anaconda Python distribution graphical libraries like Bokeh and the use of Github for collaborative development.

GBP 74.99
1

Artificial Intelligence for Autonomous Networks

Artificial Intelligence for Autonomous Networks

Artificial Intelligence for Autonomous Networks introduces the autonomous network by juxtaposing two unique technologies and communities: Networking and AI. The book reviews the technologies behind AI and software-defined network/network function virtualization highlighting the exciting opportunities to integrate those two worlds. Outlining the new frontiers for autonomous networks this book highlights their impact and benefits to consumers and enterprise customers. It also explores the potential of the autonomous network for transforming network operation cyber security enterprise services 5G and IoT infrastructure monitoring and traffic optimization and finally customer experience and care. With contributions from leading experts this book will provide an invaluable resource for network engineers software engineers artificial intelligence and machine learning researchers.

GBP 46.99
1

Geometry for the Artist

Geometry for the Artist

Geometry for the Artist is based on a course of the same name which started in the 1980s at Maharishi International University. It is aimed both at artists willing to dive deeper into geometry and at mathematicians open to learning about applications of mathematics in art. The book includes topics such as perspective symmetry topology fractals curves surfaces and more. A key part of the book’s approach is the analysis of art from a geometric point of view—looking at examples of how artists use each new topic. In addition exercises encourage students to experiment in their own work with the new ideas presented in each chapter. This book is an exceptional resource for students in a general-education mathematics course or teacher-education geometry course and since many assignments involve writing about art this text is ideal for a writing-intensive course. Moreover this book will be enjoyed by anyone with an interest in connections between mathematics and art. Features Abundant examples of artwork displayed in full color Suitable as a textbook for a general-education mathematics course or teacher-education geometry course Designed to be enjoyed by both artists and mathematicians

GBP 44.99
1

Metamodeling for Variable Annuities

Metamodeling for Variable Annuities

This book is devoted to the mathematical methods of metamodeling that can be used to speed up the valuation of large portfolios of variable annuities. It is suitable for advanced undergraduate students graduate students and practitioners. It is the goal of this book to describe the computational problems and present the metamodeling approaches in a way that can be accessible to advanced undergraduate students and practitioners. To that end the book will not only describe the theory of these mathematical approaches but also present the implementations. | Metamodeling for Variable Annuities

GBP 44.99
1

Mathematics for Engineers and Scientists

Mathematics for Engineers and Scientists

Since its original publication in 1969 Mathematics for Engineers and Scientists has built a solid foundation in mathematics for legions of undergraduate science and engineering students. It continues to do so but as the influence of computers has grown and syllabi have evolved once again the time has come for a new edition. Thoroughly revised to meet the needs of today's curricula Mathematics for Engineers and Scientists Sixth Edition covers all of the topics typically introduced to first- or second-year engineering students from number systems functions and vectors to series differential equations and numerical analysis. Among the most significant revisions to this edition are:Simplified presentation of many topics and expanded explanations that further ease the comprehension of incoming engineering studentsA new chapter on double integralsMany more exercises applications and worked examplesA new chapter introducing the MATLAB and Maple software packagesAlthough designed as a textbook with problem sets in each chapter and selected answers at the end of the book Mathematics for Engineers and Scientists Sixth Edition serves equally well as a supplemental text and for self-study. The author strongly encourages readers to make use of computer algebra software to experiment with it and to learn more about mathematical functions and the operations that it can perform.

GBP 170.00
1

Statistical Reasoning for Surgeons

Statistical Reasoning for Surgeons

Trying to read up on statistics can be like trying to decide where you want to start eating the elephant and what’s the most digestible way to get it down. This book is written to give bite-size nuggets of insight based on our experiences grappling with datasets large and small. It is intended to bridge the gap between the formal equations and the practicalities of generating a research manuscript. We won’t pretend reading it will answer all your questions but it will help explain what questions need to be asked for your study and how you can address them with both accuracy and clarity. The size detail and (ostensible) organization of this book allow for easy reading and can give a leg (or at least a half-step) up for those seeking more detailed study later. Features include: Excel sheets to allow exploration of topics raised Emphasis on intuitive explanations over formulas. Consideration of issues specific to clinical and surgical studies Our audience is someone who may or may not have enjoyed formal statistics education (that is you may have had it and not enjoyed it!) who may like seeing a more dressed-down presentation of the topics. Actual statisticians may pick this up at risk of a chuckle (with us or at us) and may find some useful ways to present topics to non-statisticians. | Statistical Reasoning for Surgeons

GBP 48.99
1

Algorithms for Next-Generation Sequencing

Algorithms for Next-Generation Sequencing

Advances in sequencing technology have allowed scientists to study the human genome in greater depth and on a larger scale than ever before – as many as hundreds of millions of short reads in the course of a few days. But what are the best ways to deal with this flood of data?Algorithms for Next-Generation Sequencing is an invaluable tool for students and researchers in bioinformatics and computational biology biologists seeking to process and manage the data generated by next-generation sequencing and as a textbook or a self-study resource. In addition to offering an in-depth description of the algorithms for processing sequencing data it also presents useful case studies describing the applications of this technology.

GBP 44.99
1

Introductory Concepts for Abstract Mathematics

Introductory Concepts for Abstract Mathematics

Beyond calculus the world of mathematics grows increasingly abstract and places new and challenging demands on those venturing into that realm. As the focus of calculus instruction has become increasingly computational it leaves many students ill prepared for more advanced work that requires the ability to understand and construct proofs. Introductory Concepts for Abstract Mathematics helps readers bridge that gap. It teaches them to work with abstract ideas and develop a facility with definitions theorems and proofs. They learn logical principles and to justify arguments not by what seems right but by strict adherence to principles of logic and proven mathematical assertions - and they learn to write clearly in the language of mathematicsThe author achieves these goals through a methodical treatment of set theory relations and functions and number systems from the natural to the real. He introduces topics not usually addressed at this level including the remarkable concepts of infinite sets and transfinite cardinal numbersIntroductory Concepts for Abstract Mathematics takes readers into the world beyond calculus and ensures their voyage to that world is successful. It imparts a feeling for the beauty of mathematics and its internal harmony and inspires an eagerness and increased enthusiasm for moving forward in the study of mathematics.

GBP 59.99
1

Graphical Methods for Data Analysis

Graphical Methods for Data Analysis

This book present graphical methods for analysing data. Some methods are new and some are old some require a computer and others only paper and pencil; but they are all powerful data analysis tools. In many situations a set of data � even a large set- can be adequately analysed through graphical methods alone. In most other situations a few well-chosen graphical displays can significantly enhance numerical statistical analyses. | Graphical Methods for Data Analysis

GBP 205.00
1

Image Processing for Cinema

Image Processing for Cinema

Image Processing for Cinema presents a detailed overview of image processing techniques that are used in practice in digital cinema. The book shows how image processing has become ubiquitous in movie-making from shooting to exhibition. It covers all the ways in which image processing algorithms are used to enhance restore adapt and convert moving images. These techniques and algorithms make the images look as good as possible while exploiting the capabilities of cameras projectors and displays. The author focuses on the ideas behind the methods rather than proofs and derivations. The first part of the text presents fundamentals on optics and color. The second part explains how cameras work and details all the image processing algorithms that are applied in-camera. With an emphasis on state-of-the-art methods that are actually used in practice the last part describes image processing algorithms that are applied offline to solve a variety of problems. The book is designed for advanced undergraduate and graduate students in applied mathematics image processing computer science and related fields. It is also suitable for academic researchers and professionals in the movie industry.

GBP 59.99
1

Statistical Methods for Mediation Confounding and Moderation Analysis Using R and SAS

Statistical Methods for Mediation Confounding and Moderation Analysis Using R and SAS

Third-variable effect refers to the effect transmitted by third-variables that intervene in the relationship between an exposure and a response variable. Differentiating between the indirect effect of individual factors from multiple third-variables is a constant problem for modern researchers. Statistical Methods for Mediation Confounding and Moderation Analysis Using R and SAS introduces general definitions of third-variable effects that are adaptable to all different types of response (categorical or continuous) exposure or third-variables. Using this method multiple third- variables of different types can be considered simultaneously and the indirect effect carried by individual third-variables can be separated from the total effect. Readers of all disciplines familiar with introductory statistics will find this a valuable resource for analysis. Key Features: Parametric and nonparametric method in third variable analysis Multivariate and Multiple third-variable effect analysis Multilevel mediation/confounding analysis Third-variable effect analysis with high-dimensional data Moderation/Interaction effect analysis within the third-variable analysis R packages and SAS macros to implement methods proposed in the book

GBP 130.00
1

Software Engineering for Science

Software Engineering for Science

Software Engineering for Science provides an in-depth collection of peer-reviewed chapters that describe experiences with applying software engineering practices to the development of scientific software. It provides a better understanding of how software engineering is and should be practiced and which software engineering practices are effective for scientific software. The book starts with a detailed overview of the Scientific Software Lifecycle and a general overview of the scientific software development process. It highlights key issues commonly arising during scientific software development as well as solutions to these problems. The second part of the book provides examples of the use of testing in scientific software development including key issues and challenges. The chapters then describe solutions and case studies aimed at applying testing to scientific software development efforts. The final part of the book provides examples of applying software engineering techniques to scientific software including not only computational modeling but also software for data management and analysis. The authors describe their experiences and lessons learned from developing complex scientific software in different domains. About the EditorsJeffrey Carver is an Associate Professor in the Department of Computer Science at the University of Alabama. He is one of the primary organizers of the workshop series on Software Engineering for Science (http://www. SE4Science. org/workshops). Neil P. Chue Hong is Director of the Software Sustainability Institute at the University of Edinburgh. His research interests include barriers and incentives in research software ecosystems and the role of software as a research object. George K. Thiruvathukal is Professor of Computer Science at Loyola University Chicago and Visiting Faculty at Argonne National Laboratory. His current research is focused on software metrics in open source mathematical and scientific software.

GBP 44.99
1

AI for Cars

AI for Cars

Artificial Intelligence (AI) is undoubtedly playing an increasingly significant role in automobile technology. In fact cars inhabit one of just a few domains where you will find many AI innovations packed into a single product. AI for Cars provides a brief guided tour through many different AI landscapes including robotics image and speech processing recommender systems and onto deep learning all within the automobile world. From pedestrian detection to driver monitoring to recommendation engines the book discusses the background research and progress thousands of talented engineers and researchers have achieved thus far and their plans to deploy this life-saving technology all over the world.

GBP 22.99
1