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Exercises in Programming Style

Exercises in Programming Style

The first edition of Exercises in Programming Style was honored as an ACM Notable Book and praised as The best programming book of the decade. This new edition retains the same presentation but has been upgraded to Python 3 and there is a new section on neural network styles. Using a simple computational task (term frequency) to illustrate different programming styles Exercises in Programming Style helps readers understand the various ways of writing programs and designing systems. It is designed to be used in conjunction with code provided on an online repository. The book complements and explains the raw code in a way that is accessible to anyone who regularly practices the art of programming. The book can also be used in advanced programming courses in computer science and software engineering programs. The book contains 40 different styles for writing the term frequency task. The styles are grouped into ten categories: historical basic function composition objects and object interactions reflection and metaprogramming adversity data-centric concurrency interactivity and neural networks. The author states the constraints in each style and explains the example programs. Each chapter first presents the constraints of the style next shows an example program and then gives a detailed explanation of the code. Most chapters also have sections focusing on the use of the style in systems design as well as sections describing the historical context in which the programming style emerged.

GBP 35.99
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Cure Models Methods Applications and Implementation

Cure Models Methods Applications and Implementation

Cure Models: Methods Applications and Implementation is the first book in the last 25 years that provides a comprehensive and systematic introduction to the basics of modern cure models including estimation inference and software. This book is useful for statistical researchers and graduate students and practitioners in other disciplines to have a thorough review of modern cure model methodology and to seek appropriate cure models in applications. The prerequisites of this book include some basic knowledge of statistical modeling survival models and R and SAS for data analysis. The book features real-world examples from clinical trials and population-based studies and a detailed introduction to R packages SAS macros and WinBUGS programs to fit some cure models. The main topics covered include the foundation of statistical estimation and inference of cure models for independent and right-censored survival data cure modeling for multivariate recurrent-event and competing-risks survival data and joint modeling with longitudinal data statistical testing for the existence and difference of cure rates and sufficient follow-up new developments in Bayesian cure models applications of cure models in public health research and clinical trials. | Cure Models Methods Applications and Implementation

GBP 35.99
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Real World AI Ethics for Data Scientists Practical Case Studies

Real World AI Ethics for Data Scientists Practical Case Studies

In the midst of the fourth industrial revolution big data is weighed in gold placing enormous power in the hands of data scientists – the modern AI alchemists. But great power comes with greater responsibility. This book seeks to shape in a practical diverse and inclusive way the ethical compass of those entrusted with big data. Being practical this book provides seven real-world case studies dealing with big data abuse. These cases span a range of topics from the statistical manipulation of research in the Cornell food lab through the Facebook user data abuse done by Cambridge Analytica to the abuse of farm animals by AI in a chapter co-authored by renowned philosophers Peter Singer and Yip Fai Tse. Diverse and inclusive given the global nature of this revolution this book provides case-by-case commentary on the cases by scholars representing non-Western ethical approaches (Buddhist Jewish Indigenous and African) as well as Western approaches (consequentialism deontology and virtue). We hope this book will be a lighthouse for those debating ethical dilemmas in this challenging and ever-evolving field. | Real World AI Ethics for Data Scientists Practical Case Studies

GBP 42.99
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Digitalization and Social Change A Guide in Critical Thinking

Digitalization and Social Change A Guide in Critical Thinking

Digitalization is shaping our everyday lives yet navigating the changes it entails can feel like trekking into the unknown where both the possibilities and the consequences are unclear and difficult to grasp. Exploring how digitalization affects all aspects of our lives from health to culture this book aims to develop and strengthen the reader’s ability to think critically about such developments. Written in a clear and concise manner with reference to science fiction and pop culture this book presents potent theoretical perspectives for understanding digitalization processes as societal change. Various exercises are included throughout to encourage readers to critically explore digitalization in their own lives. Replete with illustrations and examples this book is an accessible guide to digitalization in the modern societal context appealing to students at the undergraduate level as well as general readership. | Digitalization and Social Change A Guide in Critical Thinking

GBP 42.99
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Hidden in White Sight How AI Empowers and Deepens Systemic Racism

Hidden in White Sight How AI Empowers and Deepens Systemic Racism

Artificial Intelligence was meant to be the great social equalizer that helps promote fairness by removing human bias from the equation but is this true? Given that the policing and judicial systems can display human bias this book explores how the technology they use can also reflect these prejudices. From healthcare services to social scoring in exams to applying for and getting loans AI outcomes often restrict those most in need of these services. Through personal stories from an esteemed Black Data Scientist and AI expert this book attempts to demystify the algorithmic black box. AI pervades all aspects of modern society and affects everyone within it yet its internal biases are rarely confronted. This book advises readers on what they can do to fight against it including the introduction of a proposed AI Bill of Rights whilst also providing specific recommendations for AI developers and technologists. https://hiddeninwhitesight. com/ | Hidden in White Sight How AI Empowers and Deepens Systemic Racism

GBP 22.99
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An Illustrated Introduction to Topology and Homotopy Solutions Manual for Part 1 Topology

An Illustrated Introduction to Topology and Homotopy Solutions Manual for Part 1 Topology

This solution manual accompanies the first part of the book An Illustrated Introduction toTopology and Homotopy by the same author. Except for a small number of exercises inthe first few sections we provide solutions of the (228) odd-numbered problemsappearing in first part of the book (Topology). The primary targets of this manual are thestudents of topology. This set is not disjoint from the set of instructors of topologycourses who may also find this manual useful as a source of examples exam problems etc. | An Illustrated Introduction to Topology and Homotopy Solutions Manual for Part 1 Topology

GBP 36.99
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AI by Design A Plan for Living with Artificial Intelligence

AI by Design A Plan for Living with Artificial Intelligence

This book introduces the reader to Artificial Intelligence and its importance to our future. Campbell uses behavioural psychology explores technology economics real-life and historical examples to predict five future scenarios with AI. Illustrating through speculative fiction she describes possible futures after AI exceeds human capabilities. We are at a tipping point in history and must plan to ensure a successful co-existence with artificial intelligence. This book explains how to design for a future with AI so that rather than herald our downfall it helps us achieve a new renaissance. | AI by Design A Plan for Living with Artificial Intelligence

GBP 24.99
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Community College Mathematics Past Present and Future

Community College Mathematics Past Present and Future

This book explores the rich history of community college math with a specific focus on gatekeeper math classes. Gatekeeper math classes include courses such as college algebra introduction to statistics and all developmental math classes. For community colleges successful completion of these classes is imperative for student retention. This book presents a decade-by-decade analysis of the history of community college mathematics. The author employs a mix of conceptual empirical and quantitative research. The empirical research stems from interviews with 30 community college faculty members from seven community colleges. From the 1970s to the pandemic in the early 2020s the book explores math curricula as well as trends initiatives teaching practices and mandates that have impacted community college math. The positives and negatives of such trends initiatives and mandates are presented along with suggestions on how to apply such knowledge going forward. The author addresses the key questions: How can we build a future model for community college gatekeeper math classes that is both successful and sustainable? Additionally how can we learn from the past and the present to build such a model? This book will be ideal for students in graduate programs focusing on community college leadership or developmental education leadership as well as all those hoping to improve success rates in community college mathematics programs. | Community College Mathematics Past Present and Future

GBP 24.99
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A First Course in Machine Learning

A First Course in Machine Learning

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 new chapters put it at the forefront of the field by covering topics that have become mainstream in machine learning over the last decade. —Daniel Barbara George Mason University Fairfax Virginia USA The new edition of A First Course in Machine Learning by Rogers and Girolami is an excellent introduction to the use of statistical methods in machine learning. The book introduces concepts such as mathematical modeling inference and prediction providing ‘just in time’ the essential background on linear algebra calculus and probability theory that the reader needs to understand these concepts. —Daniel Ortiz-Arroyo Associate Professor Aalborg University Esbjerg Denmark I was impressed by how closely the material aligns with the needs of an introductory course on machine learning which is its greatest strength…Overall this is a pragmatic and helpful book which is well-aligned to the needs of an introductory course and one that I will be looking at for my own students in coming months. —David Clifton University of Oxford UK The first edition of this book was already an excellent introductory text on machine learning for an advanced undergraduate or taught masters level course or indeed for anybody who wants to learn about an interesting and important field of computer science. The additional chapters of advanced material on Gaussian process MCMC and mixture modeling provide an ideal basis for practical projects without disturbing the very clear and readable exposition of the basics contained in the first part of the book. —Gavin Cawley Senior Lecturer School of Computing Sciences University of East Anglia UK This book could be used for junior/senior undergraduate students or first-year graduate students as well as individuals who want to explore the field of machine learning…The book introduces not only the concepts but the underlying ideas on algorithm implementation from a critical thinking perspective. —Guangzhi Qu Oakland University Rochester Michigan USA

GBP 39.99
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An Introduction to Metric Spaces

An Introduction to Metric Spaces

This book serves as a textbook for an introductory course in metric spaces for undergraduate or graduate students. The goal is to present the basics of metric spaces in a natural and intuitive way and encourage students to think geometrically while actively participating in the learning of this subject. In this book the authors illustrated the strategy of the proofs of various theorems that motivate readers to complete them on their own. Bits of pertinent history are infused in the text including brief biographies of some of the central players in the development of metric spaces. The textbook is divided into seven chapters that contain the main materials on metric spaces; namely introductory concepts completeness compactness connectedness continuous functions and metric fixed point theorems with applications. Some of the noteworthy features of this book include · Diagrammatic illustrations that encourage readers to think geometrically · Focus on systematic strategy to generate ideas for the proofs of theorems · A wealth of remarks observations along with a variety of exercises · Historical notes and brief biographies appearing throughout the text | An Introduction to Metric Spaces

GBP 32.99
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Clinical Data Quality Checks for CDISC Compliance Using SAS

Clinical Data Quality Checks for CDISC Compliance Using SAS

Clinical Data Quality Checks for CDISC Compliance using SAS is the first book focused on identifying and correcting data quality and CDISC compliance issues with real-world innovative SAS programming techniques such as Proc SQL metadata and macro programming. Learn to master Proc SQL’s subqueries and summary functions for multi-tasking process. Drawing on his more than 25 years’ experience in the pharmaceutical industry the author provides a unique approach that empowers SAS programmers to take control of data quality and CDISC compliance. This book helps you create a system of SDTM and ADaM checks that can be tracked for continuous improvement. How often have you encountered issues such as missing required variables duplicate records invalid derived variables and invalid sequence of two dates? With the SAS programming techniques introduced in this book you can start to monitor these and more complex data and CDISC compliance issues. With increased standardization in SDTM and ADaM specifications and data values codelist dictionaries can be created for better organization planning and maintenance. This book includes a SAS program to create excel files containing unique values from all SDTM and ADaM variables as columns. In addition another SAS program compares SDTM and ADaM codelist dictionaries with codelists from define. xml specifications. Having tools to automate this process greatly saves time from doing it manually. Features SDTMs and ADaMs Vitals SDTMs and ADaMs Data CDISC Specifications Compliance CDISC Data Compliance Protocol Compliance Codelist Dictionary Compliance

GBP 39.99
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Introduction to Math Olympiad Problems

Introduction to Math Olympiad Problems

Introduction to Math Olympiad Problems aims to introduce high school students to all the necessary topics that frequently emerge in international Math Olympiad competitions. In addition to introducing the topics the book will also provide several repetitive-type guided problems to help develop vital techniques in solving problems correctly and efficiently. The techniques employed in the book will help prepare students for the topics they will typically face in an Olympiad-style event but also for future college mathematics courses in Discrete Mathematics Graph Theory Differential Equations Number Theory and Abstract Algebra. Features: Numerous problems designed to embed good practice in readers and build underlying reasoning analysis and problem-solving skills Suitable for advanced high school students preparing for Math Olympiad competitions

GBP 24.99
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Business Financial Planning with Microsoft Excel

Business Financial Planning with Microsoft Excel

Business Finance Planning with Microsoft® Excel® shows how to visualize plan and put into motion an idea for creating a start-up company. Microsoft Excel is a tool that makes it easier to build a business financial planning process for a new business venture. With an easy-to follow structure the book flows as a six-step process: Presenting a case study of a business start-up Creating goals and objectives Determining expenses from those goals and objectives Estimating potential sales revenue based on what competitors charge their customers Predicting marketing costs Finalizing the financial analysis with a of financial statements. Written around an IT startup case study the book presents a host of Excel worksheets describing the case study along with accompanying blank forms. Readers can use these forms in their own businesses so they can build parts of their own business plans as they go. This is intended to be a practical guide that teaches and demonstrates by example in the end presenting a usable financial model to build and tweak a financial plan with a set of customizable Excel worksheets. The book uses practical techniques to help with the planning processing. These include applying a SWOT (strengths weaknesses opportunities and threats) matrix to evaluate a business idea and SMART (Specific Measurable Achievable Relevant and Time-Bound) objectives to link together goals. As the book concludes readers will be able to develop their own income statement balance sheet and the cash-flow statement for a full analysis of their new business ideas. Worksheets are available to download from: https://oracletroubleshooter. com/business-finance-planning/app/ | Business Financial Planning with Microsoft Excel

GBP 34.99
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Flexible Imputation of Missing Data Second Edition

Flexible Imputation of Missing Data Second Edition

Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes like deletion or mean imputation only work under highly restrictive conditions which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem. This is the second edition of a popular book on multiple imputation focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field. This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. The book sharpens the reader’s intuition on how to think about missing data and provides all the tools needed to execute a well-grounded quantitative analysis in the presence of missing data. | Flexible Imputation of Missing Data Second Edition

GBP 38.99
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Intelligent Automation Bridging the Gap between Business and Academia

Intelligent Automation Bridging the Gap between Business and Academia

Since prehistoric times humans have invented ways to simplify daily activities to improve productivity. The most recent milestone in this journey is robotic process automation (RPA) helping to build software robots that can be leveraged to automate mundane and repetitive tasks that can be labor-intensive and prone to errors. In recent years RPA has been integrated with emerging artificial intelligence (AI) and machine learning (ML) technologies to create what is referred to as intelligent automation (IA) emulating human actions and decision-making abilities. This book addresses the critical questions about the rise usage and future of IA practices. This book is structured by general personas considered as its primary target audience ranging from: Early-stage practitioners seeking to learn effective management of IA programs Established IA practitioners seeking to drive maturity and scale Business leaders seeking to understand how to drive business value using IA Practitioners or academicians seeking to collaborate This book is strongly recommended for practitioners seeking to plan implement and scale IA practices in their organization and for researchers and students who intend to study strategy implementation and management of IA practice to accelerate the digital transformation agenda. | Intelligent Automation Bridging the Gap between Business and Academia

GBP 42.99
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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
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Environmental and Ecological Statistics with R

Environmental and Ecological Statistics with R

Emphasizing the inductive nature of statistical thinking Environmental and Ecological Statistics with R Second Edition connects applied statistics to the environmental and ecological fields. Using examples from published works in the ecological and environmental literature the book explains the approach to solving a statistical problem covering model specification parameter estimation and model evaluation. It includes many examples to illustrate the statistical methods and presents R code for their implementation. The emphasis is on model interpretation and assessment and using several core examples throughout the book the author illustrates the iterative nature of statistical inference. The book starts with a description of commonly used statistical assumptions and exploratory data analysis tools for the verification of these assumptions. It then focuses on the process of building suitable statistical models including linear and nonlinear models classification and regression trees generalized linear models and multilevel models. It also discusses the use of simulation for model checking and provides tools for a critical assessment of the developed models. The second edition also includes a complete critique of a threshold model. Environmental and Ecological Statistics with R Second Edition focuses on statistical modeling and data analysis for environmental and ecological problems. By guiding readers through the process of scientific problem solving and statistical model development it eases the transition from scientific hypothesis to statistical model.

GBP 39.99
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Biomarker Analysis in Clinical Trials with R

Biomarker Analysis in Clinical Trials with R

The world is awash in data. This volume of data will continue to increase. In the pharmaceutical industry much of this data explosion has happened around biomarker data. Great statisticians are needed to derive understanding from these data. This book will guide you as you begin the journey into communicating understanding and synthesizing biomarker data. From the Foreword Jared Christensen Vice President Biostatistics Early Clinical Development Pfizer Inc. Biomarker Analysis in Clinical Trials with R offers practical guidance to statisticians in the pharmaceutical industry on how to incorporate biomarker data analysis in clinical trial studies. The book discusses the appropriate statistical methods for evaluating pharmacodynamic predictive and surrogate biomarkers for delivering increased value in the drug development process. The topic of combining multiple biomarkers to predict drug response using machine learning is covered. Featuring copious reproducible code and examples in R the book helps students researchers and biostatisticians get started in tackling the hard problems of designing and analyzing trials with biomarkers. Features:Analysis of pharmacodynamic biomarkers for lending evidence target modulation. Design and analysis of trials with a predictive biomarker. Framework for analyzing surrogate biomarkers. Methods for combining multiple biomarkers to predict treatment response. Offers a biomarker statistical analysis plan. R code data and models are given for each part: including regression models for survival and longitudinal data as well as statistical learning models such as graphical models and penalized regression models.

GBP 39.99
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R Markdown Cookbook

R Markdown Cookbook

This new book written by the developers of R Markdown is an essential reference that will help users learn and make full use of the software. Those new to R Markdown will appreciate the short practical examples that address the most common issues users encounter. Frequent users will also benefit from the wide ranging tips and tricks that expose ‘hidden’ features support customization and demonstrate the many new and varied applications of the software. After reading this book users will learn how to: Enhance your R Markdown content with diagrams citations and dynamically generated text Streamline your workflow with child documents code chunk references and caching Control the formatting and layout with Pandoc markdown syntax or by writing custom HTML and LaTeX templates Utilize chunk options and hooks to fine-tune how your code is processed Switch between different language engineers to seamlessly incorporate python D3 and more into your analysis | R Markdown Cookbook

GBP 28.99
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Operating System Design The Xinu Approach Second Edition

Operating System Design The Xinu Approach Second Edition

An Update of the Most Practical A-to-Z Operating System BookWidely lauded for avoiding the typical black box approach found in other operating system textbooks the first edition of this bestselling book taught readers how an operating system works and explained how to build it from the ground up. Continuing to follow a logical pattern for system design Operating System Design: The Xinu Approach Second Edition removes the mystery from operating system design and consolidates the body of material into a systematic discipline. It presents a hierarchical design paradigm that organizes major operating system components in an orderly understandable manner. The book guides readers through the construction of a conventional process-based operating system using practical straightforward primitives. It gives the implementation details of one set of primitives usually the most popular set. Once readers understand how primitives can be implemented on conventional hardware they can then easily implement alternative versions. The text begins with a bare machine and proceeds step-by-step through the design and implementation of Xinu which is a small elegant operating system that supports dynamic process creation dynamic memory allocation network communication local and remote file systems a shell and device-independent I/O functions. The Xinu code runs on many hardware platforms. This second edition has been completely rewritten to contrast operating systems for RISC and CISC processors. Encouraging hands-on experimentation the book provides updated code throughout and examples for two low-cost experimenter boards: BeagleBone Black from ARM and Galileo from Intel. | Operating System Design The Xinu Approach Second Edition

GBP 39.99
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A Pen and Paper Introduction to Statistics

A Pen and Paper Introduction to Statistics

Statistics is central in the biosciences social sciences and other disciplines yet many students often struggle to learn how to perform statistical tests and to understand how and why statistical tests work. Although there are many approaches to teaching statistics a common framework exists between them: starting with probability and distributions then sampling from distribution and descriptive statistics and later introducing both simple and complex statistical tests typically ending with regression analysis (linear models). This book proposes to reverse the way statistics is taught by starting with the introduction of linear models. Today many statisticians know that the one unifying principle of statistical tests is that most of them are instances of linear models. This teaching method has two advantages: all statistical tests in a course can be presented under the same unifying framework simplifying things; second linear models can be expressed as lines over squared paper replacing any equation with a drawing. This book explains how and why statistics works without using a single equation just lines and squares over grid paper. The reader will have the opportunity to work through the examples and compute sums of squares by just drawing and counting and finally evaluating whether observed differences are statistically significant by using the tables provided. Intended for students scientists and those with little prior knowledge of statistics this book is for all with simple and clear examples computations and drawings helping the reader to not only do statistical tests but also understand statistics. | A Pen and Paper Introduction to Statistics

GBP 31.99
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Advanced Survival Models

Advanced Survival Models

Survival data analysis is a very broad field of statistics encompassing a large variety of methods used in a wide range of applications and in particular in medical research. During the last twenty years several extensions of classical survival models have been developed to address particular situations often encountered in practice. This book aims to gather in a single reference the most commonly used extensions such as frailty models (in case of unobserved heterogeneity or clustered data) cure models (when a fraction of the population will not experience the event of interest) competing risk models (in case of different types of event) and joint survival models for a time-to-event endpoint and a longitudinal outcome. Features Presents state-of-the art approaches for different advanced survival models including frailty models cure models competing risk models and joint models for a longitudinal and a survival outcome Uses consistent notation throughout the book for the different techniques presented Explains in which situation each of these models should be used and how they are linked to specific research questions Focuses on the understanding of the models their implementation and their interpretation with an appropriate level of methodological development for masters students and applied statisticians Provides references to existing R packages and SAS procedure or macros and illustrates the use of the main ones on real datasets This book is primarily aimed at applied statisticians and graduate students of statistics and biostatistics. It can also serve as an introductory reference for methodological researchers interested in the main extensions of classical survival analysis.

GBP 42.99
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Teaching Mathematics at a Technical College

Teaching Mathematics at a Technical College

Not much has been written about technical colleges especially teaching mathematics at one. Much had been written about community college mathematics. This book addresses this disparity. Mathematics is a beautiful subject worthy to be taught at the technical college level. The author sheds light on technical colleges and their importance in the higher education system. Technical colleges area more affordable for students and provide many career opportunities. These careers are becoming or have become as lucrative as careers requiring a four-year-degree. The interest in technical college education is likely to continue to grow. Mathematics like all other classes is a subject that needs time energy and dedication to learn. For an instructor it takes many years of hard work and dedication just to be able to teach the subject. Students should not be expected to learn the mathematics overnight. As instructors we need to be open honest and put forth our very best to our students so that they can see that they are able to succeed in whatever is placed in front of them. This book hopes to encourage such an effort. A notable percentage of students who are receiving associate degrees will go through at least one of more mathematics courses. These students should not be forgotten about—their needs are similar to any student who is required to take a mathematics course to earn a degree. This book offers insight into teaching mathematics at a technical college. It is also a source for students to turn toward when they are feeling dread in taking a mathematics course. Mathematics instructors want to help students succeed. If they put forth their best effort and us ours we can all work as one team to get the student through the course and onto chasing their dreams. Though this book focuses on teaching mathematics some chapters expand to focus on teaching in general. The overall hope is the reader will be inspired by the great work that is happening at technical colleges all around the country. Technical college can be should be and is the backbone of the American working class.

GBP 22.99
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Security for Software Engineers

Security for Software Engineers

Security for Software Engineers is designed to introduce security concepts to undergraduate software engineering students. The book is divided into four units each targeting activities that a software engineer will likely be involved in within industry. The book explores the key areas of attack vectors code hardening privacy and social engineering. Each topic is explored from a theoretical and a practical-application standpoint. Features:Targets software engineering students - one of the only security texts to target this audience. Focuses on the white-hat side of the security equation rather than the black-hat side. Includes many practical and real-world examples that easily translate into the workplace. Covers a one-semester undergraduate course. Describes all aspects of computer security as it pertains to the job of a software engineer and presents problems similar to that which an engineer will encounter in the industry. This text will equip students to make knowledgeable security decisions be productive members of a security review team and write code that protects a user’s information assets.

GBP 39.99
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Time Series A First Course with Bootstrap Starter

Time Series A First Course with Bootstrap Starter

Time Series: A First Course with Bootstrap Starter provides an introductory course on time series analysis that satisfies the triptych of (i) mathematical completeness (ii) computational illustration and implementation and (iii) conciseness and accessibility to upper-level undergraduate and M. S. students. Basic theoretical results are presented in a mathematically convincing way and the methods of data analysis are developed through examples and exercises parsed in R. A student with a basic course in mathematical statistics will learn both how to analyze time series and how to interpret the results. The book provides the foundation of time series methods including linear filters and a geometric approach to prediction. The important paradigm of ARMA models is studied in-depth as well as frequency domain methods. Entropy and other information theoretic notions are introduced with applications to time series modeling. The second half of the book focuses on statistical inference the fitting of time series models as well as computational facets of forecasting. Many time series of interest are nonlinear in which case classical inference methods can fail but bootstrap methods may come to the rescue. Distinctive features of the book are the emphasis on geometric notions and the frequency domain the discussion of entropy maximization and a thorough treatment of recent computer-intensive methods for time series such as subsampling and the bootstrap. There are more than 600 exercises half of which involve R coding and/or data analysis. Supplements include a website with 12 key data sets and all R code for the book's examples as well as the solutions to exercises. | Time Series A First Course with Bootstrap Starter

GBP 38.99
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