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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

Solution Techniques for Elementary Partial Differential Equations

Algorithms for Next-Generation Sequencing

Introduction to R for Social Scientists A Tidy Programming Approach

Data Driven Science for Clinically Actionable Knowledge in Diseases

Equivalence and Noninferiority Tests for Quality Manufacturing and Test Engineers

Programming for Hybrid Multi/Manycore MPP Systems

Programming for Hybrid Multi/Manycore MPP Systems

Ask not what your compiler can do for you ask what you can do for your compiler. John Levesque Director of Cray’s Supercomputing Centers of ExcellenceThe next decade of computationally intense computing lies with more powerful multi/manycore nodes where processors share a large memory space. These nodes will be the building block for systems that range from a single node workstation up to systems approaching the exaflop regime. The node itself will consist of 10’s to 100’s of MIMD (multiple instruction multiple data) processing units with SIMD (single instruction multiple data) parallel instructions. Since a standard affordable memory architecture will not be able to supply the bandwidth required by these cores new memory organizations will be introduced. These new node architectures will represent a significant challenge to application developers. Programming for Hybrid Multi/Manycore MPP Systems attempts to briefly describe the current state-of-the-art in programming these systems and proposes an approach for developing a performance-portable application that can effectively utilize all of these systems from a single application. The book starts with a strategy for optimizing an application for multi/manycore architectures. It then looks at the three typical architectures covering their advantages and disadvantages. The next section of the book explores the other important component of the target—the compiler. The compiler will ultimately convert the input language to executable code on the target and the book explores how to make the compiler do what we want. The book then talks about gathering runtime statistics from running the application on the important problem sets previously discussed. How best to utilize available memory bandwidth and virtualization is covered next along with hybridization of a program. The last part of the book includes several major applications and examines future hardware advancements and how the application developer may prepare for those advancements.

GBP 44.99
1

Applied Linear Regression for Longitudinal Data With an Emphasis on Missing Observations

Probability and Statistics for Data Science Math + R + Data

Probability and Statistics for Computer Scientists

Probability and Statistics for Computer Scientists

Praise for the Second Edition: The author has done his homework on the statistical tools needed for the particular challenges computer scientists encounter. [He] has taken great care to select examples that are interesting and practical for computer scientists. . The content is illustrated with numerous figures and concludes with appendices and an index. The book is erudite and … could work well as a required text for an advanced undergraduate or graduate course. Computing Reviews Probability and Statistics for Computer Scientists Third Edition helps students understand fundamental concepts of Probability and Statistics general methods of stochastic modeling simulation queuing and statistical data analysis; make optimal decisions under uncertainty; model and evaluate computer systems; and prepare for advanced probability-based courses. Written in a lively style with simple language and now including R as well as MATLAB this classroom-tested book can be used for one- or two-semester courses. Features: Axiomatic introduction of probability Expanded coverage of statistical inference and data analysis including estimation and testing Bayesian approach multivariate regression chi-square tests for independence and goodness of fit nonparametric statistics and bootstrap Numerous motivating examples and exercises including computer projects Fully annotated R codes in parallel to MATLAB Applications in computer science software engineering telecommunications and related areas In-Depth yet Accessible Treatment of Computer Science-Related TopicsStarting with the fundamentals of probability the text takes students through topics heavily featured in modern computer science computer engineering software engineering and associated fields such as computer simulations Monte Carlo methods stochastic processes Markov chains queuing theory statistical inference and regression. It also meets the requirements of the Accreditation Board for Engineering and Technology (ABET). About the Author Michael Baron is David Carroll Professor of Mathematics and Statistics at American University in Washington D. C. He conducts research in sequential analysis and optimal stopping change-point detection Bayesian inference and applications of statistics in epidemiology clinical trials semiconductor manufacturing and other fields. M. Baron is a Fellow of the American Statistical Association and a recipient of the Abraham Wald Prize for the best paper in Sequential Analysis and the Regents Outstanding Teaching Award. M. Baron holds a Ph. D. in statistics from the University of Maryland. In his turn he supervised twelve doctoral students mostly employed on academic and research positions.

GBP 99.99
1

Search Engine Optimization and Marketing A Recipe for Success in Digital Marketing

Search Engine Optimization and Marketing A Recipe for Success in Digital Marketing

Search Engine Optimization and Marketing: A Recipe for Success in Digital Marketing analyzes the web traffic for online promotion that includes search engine optimization and search engine marketing. After careful analysis of the nuances of the semantic web of search engine optimization (SEO) and its practical set up readers can put their best foot forward for SEO setup link-building for SERP establishment various methods with requisite algorithms and programming codes with process inferences. The book offers comprehensive coverage of essential topics including: • The concept of SEM and SEO • The mechanism of crawler program concepts of keywords • Keyword generation tools • Page ranking mechanism and indexing • Concepts of title meta alt tags • Concepts of PPC/PPM/CTR • SEO/SEM strategies • Anchor text and setting up • Query-based search While other books are focused on the traditional explanation of digital marketing theoretical features of SEO and SEM for keyword set up with link-building this book focuses on the practical applications of the above-mentioned concepts for effective SERP generation. Another unique aspect of this book is its abundance of handy workarounds to set up the techniques for SEO a topic too often neglected by other works in the field. This book is an invaluable resource for social media analytics researchers and digital marketing students. | Search Engine Optimization and Marketing A Recipe for Success in Digital Marketing

GBP 105.00
1

Design of Experiments for Agriculture and the Natural Sciences

Design of Experiments for Agriculture and the Natural Sciences

Written to meet the needs of both students and applied researchers Design of Experiments for Agriculture and the Natural Sciences Second Edition serves as an introductory guide to experimental design and analysis. Like the popular original this thorough text provides an understanding of the logical underpinnings of design and analysis by selecting and discussing only those carefully chosen designs that offer the greatest utility. However it improves on the first edition by adhering to a step-by-step process that greatly improves accessibility and understanding. Real problems from different areas of agriculture and science are presented throughout to show how practical issues of design and analysis are best handled. Completely revised to greatly enhance readability this new edition includes:A new chapter on covariance analysis to help readers reduce errors while enhancing their ability to examine covariances among selected variablesExpanded material on multiple regression and variance analysisAdditional examples problems and case studiesA step-by-step Minitab® guide to help with data analysisIntended for those in the agriculture environmental and natural science fields as well as statisticians this text requires no previous exposure to analysis of variance although some familiarity with basic statistical fundamentals is assumed. In keeping with the book's practical orientation numerous workable problems are presented throughout to reinforce the reader's ability to creatively apply the principles and concepts in any given situation.

GBP 44.99
1

Recent Advances in Security Privacy and Trust for Internet of Things (IoT) and Cyber-Physical Systems (CPS)

Recent Advances in Security Privacy and Trust for Internet of Things (IoT) and Cyber-Physical Systems (CPS)

Security privacy and trust in the Internet of Things (IoT) and CPS (Cyber-Physical Systems) are different from conventional security as concerns revolve around the collection and aggregation of data or transmission of data over the network. Analysis of cyber-attack vectors and the provision of appropriate mitigation techniques are essential research areas for these systems. Adoption of best practices and maintaining a balance between ease of use and security are again crucial for the effective performance of these systems. Recent Advances in Security Privacy and Trust for Internet of Things (IoT) and Cyber-Physical Systems (CPS) discusses and presents techniques and methodologies as well as a wide range of examples and illustrations to effectively show the principles algorithms challenges and applications of security privacy and trust for IoT and CPS. Book features: Introduces new directions for research development and engineering security privacy and trust of IoT and CPS Includes a wealth of examples and illustrations to effectively demonstrate the principles algorithms challenges and applications Covers most of the important security aspects and current trends not present in other reference books This book will also serve as an excellent reference in security privacy and trust of IoT and CPS for professionals in this fast-evolving and critical field. The chapters present high-quality contributions from researchers academics and practitioners from various national and international organizations and universities.

GBP 48.99
1

C++ for Financial Mathematics

Python for Bioinformatics

Geometry for the Artist

Artificial Intelligence for Autonomous Networks

Metamodeling for Variable Annuities

Numerical Methods for Finance

Mathematics for Engineers and Scientists

Statistical Reasoning for Surgeons

Image Processing for Cinema

Introductory Concepts for Abstract Mathematics

Graphical Methods for Data Analysis