This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you're comfortable with Python and its libraries, including pandas and scikit-learn, you'll be able to address specific problems such as loading data, handling text or numerical data, model selection, and dimensionality reduction and many other topics. Each recipe includes code that you can copy and paste into a toy dataset to ensure that it actually works. From there, you can insert, combine, or adapt the code to help construct your application. Recipes also include a discussion that explains the solution and provides meaningful context. This cookbook takes you beyond theory and concepts by providing the nuts and bolts you need to construct working machine learning applications. You'll find recipes for: Vectors, matrices, and arrays Handling numerical and categorical data, text, images, and dates and times Dimensionality reduction using feature extraction or feature selection Model evaluation and selection Linear and logical regression, trees and forests, and k-nearest neighbors Support vector machines (SVM), naive Bayes, clustering, and neural networks Saving and loading trained models

This book is the first dedicated to linguistic parsing - the processing of natural language according to the rules of a formal grammar - in the Minimalist Program. While Minimalism has been at the forefront of generative grammar for several decades, it often remains inaccessible to computer scientists and others in adjacent fields. This volume makes connections with standard computational architectures, provides efficient implementations of some fundamental minimalist accounts of syntax, explores implementations of recent theoretical proposals, and explores correlations between posited structures and measures of neural activity during human language comprehension. These studies will appeal to graduate students and researchers in formal syntax, computational linguistics, psycholinguistics, and computer science.

Build a Keras model to scale and deploy on a Kubernetes cluster We have seen an exponential growth in the use of Artificial Intelligence (AI) over last few years. AI is becoming the new electricity and is touching every industry from retail to manufacturing to healthcare to entertainment. Within AI, were seeing a particular growth in Machine Learning (ML) and Deep Learning (DL) applications. ML is all about learning relationships from labeled (Supervised) or unlabeled data (Unsupervised). DL has many layers of learning and can extract patterns from unstructured data like images, video, audio, etc. Keras to Kubernetes: The Journey of a Machine Learning Model to Production takes you through real-world examples of building DL models in Keras for recognizing product logos in images and extracting sentiment from text. You will then take that trained model and package it as a web application container before learning how to deploy this model at scale on a Kubernetes cluster. You will understand the different practical steps involved in real-world ML implementations which go beyond the algorithms. Find hands-on learning examples Learn to uses Keras and Kubernetes to deploy Machine Learning models Discover new ways to collect and manage your image and text data with Machine Learning Reuse examples as-is to deploy your models Understand the ML model development lifecycle and deployment to production If youre ready to learn about one of the most popular DL frameworks and build production applications with it, youve come to the right place!

Focusing exclusively on the Remote System Explorer (RSE) within the popular WebSphere Development Studio Client (WDSC), this comprehensive study contains both technical and practical tutorials. Allowing developers to use modern techniques within several programs, this survey covers topics such as getting started, terminology, installation, managing i5/OS objects and members, editing, compiling, and debugging. Each chapter features key views, actions, keyboard shortcuts, and troubleshooting tips. Illustrated with countless examples and detailed screen shots, this reference makes the RSE accessible for any developer.

Get up to speed with Apache Drill, an extensible distributed SQL query engine that reads massive datasets in many popular file formats such as Parquet, JSON, and CSV. Drill reads data in HDFS or in cloud-native storage such as S3 and works with Hive metastores along with distributed databases such as HBase, MongoDB, and relational databases. Drill works everywhere: on your laptop or in your largest cluster. In this practical book, Drill committers Charles Givre and Paul Rogers show analysts and data scientists how to query and analyze raw data using this powerful tool. Data scientists today spend about 80% of their time just gathering and cleaning data. With this book, you'll learn how Drill helps you analyze data more effectively to drive down time to insight. Use Drill to clean, prepare, and summarize delimited data for further analysis Query file types including logfiles, Parquet, JSON, and other complex formats Query Hadoop, relational databases, MongoDB, and Kafka with standard SQL Connect to Drill programmatically using a variety of languages Use Drill even with challenging or ambiguous file formats Perform sophisticated analysis by extending Drill's functionality with user-defined functions Facilitate data analysis for network security, image metadata, and machine learning

This Pocket Guide provides a concise explanation of the nature, content and aim of ISO/IEC 20000: 2011. It brings ISO/IEC 20000-1: 2011 within reach of a vast international audience by providing the key elements of this important standard in a short, easy to read Pocket Guide:

it promote the awareness and the acceptability of ISO/IEC 20000-1: 2011as a valid standard for IT Services organizations;

it supports ISO/IEC 20000-1: 2011training and certification;

it is a quick reference to the core content of ISO/IEC 20000-1: 2011, for practitioners.

ISO/IEC 20000: 2011: A Pocket Guide is ideal for a broad range of practitioners, trainers and students, who work in IT as well as in other environments, ranging from experienced experts in (IT) service organizations, to those who are looking for a suitable approach to quality improvement issues.

The New York Times Science Bestseller from Robert Wachter, Modern Healthcare's #1 Most Influential Physician-Executive in the US While modern medicine produces miracles, it also delivers care that is too often unsafe, unreliable, unsatisfying, and impossibly expensive. For the past few decades, technology has been touted as the cure for all of healthcare's ills. But medicine stubbornly resisted computerization - until now. Over the past five years, thanks largely to billions of dollars in federal incentives, healthcare has finally gone digital. Yet once clinicians started using computers to actually deliver care, it dawned on them that something was deeply wrong. Why were doctors no longer making eye contact with their patients? How could one of America's leading hospitals give a teenager a 39-fold overdose of a common antibiotic, despite a state-of-the-art computerized prescribing system? How could a recruiting ad for physicians tout the absence of an electronic medical record as a major selling point? Logically enough, we've pinned the problems on clunky software, flawed implementations, absurd regulations, and bad karma. It was all of those things, but it was also something far more complicated. And far more interesting . . . Written with a rare combination of compelling stories and hard-hitting analysis by one of the nation's most thoughtful physicians, The Digital Doctor examines healthcare at the dawn of its computer age. It tackles the hard questions, from how technology is changing care at the bedside to whether government intervention has been useful or destructive. And it does so with clarity, insight, humor, and compassion. Ultimately, it is a hopeful story. "We need to recognize that computers in healthcare don't simply replace my doctor's scrawl with Helvetica 12," writes the author Dr. Robert Wachter. "Instead, they transform the work, the people who do it, and their relationships with each other and with patients. . . . Sure, we should have thought of this sooner. But it's not too late to get it right." This riveting book offers the prescription for getting it right, making it essential reading for everyone - patient and provider alike - who cares about our healthcare system.

Computers now impact almost every aspect of our lives, from our social interactions to the safety and performance of our cars. How did this happen in such a short time? And this is just the beginning. . . . In this book, Tony Hey and Gyuri Papay lead us on a journey from the early days of computers in the 1930s to the cutting-edge research of the present day that will shape computing in the coming decades. Along the way, they explain the ideas behind hardware, software, algorithms, Moore's Law, the birth of the personal computer, the Internet and the Web, the Turing Test, Jeopardy's Watson, World of Warcraft, spyware, Google, Facebook, and quantum computing. This book also introduces the fascinating cast of dreamers and inventors who brought these great technological developments into every corner of the modern world. This exciting and accessible introduction will open up the universe of computing to anyone who has ever wondered where his or her smartphone came from."

Disk-Based Algorithms for Big Data is a product of recent advances in the areas of big data, data analytics, and the underlying file systems and data management algorithms used to support the storage and analysis of massive data collections. The book discusses hard disks and their impact on data management, since Hard Disk Drives continue to be common in large data clusters. It also explores ways to store and retrieve data though primary and secondary indices. This includes a review of different in-memory sorting and searching algorithms that build a foundation for more sophisticated on-disk approaches like mergesort, B-trees, and extendible hashing. Following this introduction, the book transitions to more recent topics, including advanced storage technologies like solid-state drives and holographic storage; peer-to-peer (P2P) communication; large file systems and query languages like Hadoop/HDFS, Hive, Cassandra, and Presto; and NoSQL databases like Neo4j for graph structures and MongoDB for unstructured document data. Designed for senior undergraduate and graduate students, as well as professionals, this book is useful for anyone interested in understanding the foundations and advances in big data storage and management, and big data analytics. About the Author Dr. Christopher G. Healey is a tenured Professor in the Department of Computer Science and the Goodnight Distinguished Professor of Analytics in the Institute for Advanced Analytics, both at North Carolina State University in Raleigh, North Carolina. He has published over 50 articles in major journals and conferences in the areas of visualization, visual and data analytics, computer graphics, and artificial intelligence. He is a recipient of the National Science Foundation's CAREER Early Faculty Development Award and the North Carolina State University Outstanding Instructor Award. He is a Senior Member of the Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE), and an Associate Editor of ACM Transaction on Applied Perception, the leading worldwide journal on the application of human perception to issues in computer science.

Providing an end-to-end view of how modern web applications are built, Dynamic Web Application Development takes a cohesive approach to building a software architecture from core components. It tells a development story by taking you right through from analysis and design, learning the core technologies, and tying them together using standard tools patterns and frameworks without straying into detail or trying to cover too many alternatives. Using PHP scripting and the MySQL database management system, this is a contemporary and well targeted coverage of important areas of web application development including Ajax, , adaptive markup, web application frameworks, standards and conformance, accessibility and security issues. It shows you how to build functionality into a website using a variety of technologies. These will work as a basic framework from which you will be able to explore more challenging developments such as porting applications to mobile devices and including more Web 2.0 features. An ideal text for web programming courses, this book will help you whether you are a student or need to reskill and want a dependable and accessible self-study package.

Understanding Computers in a Changing Society gives your students a classic introduction to computer concepts with a modern twist! Known for its emphasis on basic computer concepts and societal issues, this text makes concepts relevant to today's career-focused students and has increased emphasis on mobile computing and related issues such as mobile commerce and mobile security.

This third edition capitalizes on the success of the previous editions and leverages the important advancements in visualization, data analysis, and sharing capabilities that have emerged in recent years. It serves as an accelerated guide to decision support designs for consultants, service professionals and students. This 'fast track' enables a ramping up of skills in Excel for those who may have never used it to reach a level of mastery that will allow them to integrate Excel with widely available associated applications, make use of intelligent data visualization and analysis techniques, automate activity through basic VBA designs, and develop easy-to-use interfaces for customizing use. The content of this edition has been completely restructured and revised, with updates that correspond with the latest versions of software and references to contemporary add-in development across platforms. It also features best practices in design and analytical consideration, including methodical discussions of problem structuring and evaluation, as well as numerous case examples from practice.

As we use the Web for social networking, shopping, and news, we leave a personal trail. These days, linger over a Web page selling lamps, and they will turn up at the advertising margins as you move around the Internet, reminding you, tempting you to make that purchase. Search engines such as Google can now look deep into the data on the Web to pull out instances of the words you are looking for. And there are pages that collect and assess information to give you a snapshot of changing political opinion. These are just basic examples of the growth of "Web intelligence", as increasingly sophisticated algorithms operate on the vast and growing amount of data on the Web, sifting, selecting, comparing, aggregating, correcting; following simple but powerful rules to decide what matters. While original optimism for Artificial Intelligence declined, this new kind of machine intelligence is emerging as the Web grows ever larger and more interconnected. Gautam Shroff takes us on a journey through the computer science of search, natural language, text mining, machine learning, swarm computing, and semantic reasoning, from Watson to self-driving cars. This machine intelligence may even mimic at a basic level what happens in the brain.

Each book is summarised to convey a brief idea of what each one has to offer the interested reader, while a 'Speed Read' for each book delivers a quick sense of what each book is like to read and a highly compressed summary of the main points of the book in question. The titles covered include thought-provoking classics on psychology, mindfulness, rationality, the brain, mathematical and economic thought and practical philosophy. The selection includes books about self-improvement as well as historically interesting accounts of how the mind works. Titles included go back as far as the Epictetus classic The Enchiridion and Bertrand Russell's charming The ABC of Relativity, and proceed through classics such as Edward de Bono's Lateral Thinking and into the digital era with titles such as The Shallows and Big Data. The books are arranged chronologically, which draws attention to some of the interesting juxtapositions and connections between them. Some of the titles included are: Freakonomics, by Steven D. Levitt; Blink: The Power of Thinking Without Thinking, by Malcolm Gladwell; Sapiens: A Brief History of Humankind, by Yuval Noah Harari; The Organized Mind: Thinking Straight in the Age of Information Overload, by Daniel J. Levitin; The Descent of Man, by Grayson Perry; How the Mind Works, by Steven Pinker; Black Box Thinking: Why Some People Never Learn from Their Mistakes - But Some Do, by Matthew Syed; We Should All Be Feminists, by Chimamanda Ngozi Adichie; Guns, Germs, and Steel: The Fates of Human Societies, by Jared Diamond; The Black Swan: The Impact of the Highly Improbable, by Nassim Nicholas Taleb; Man's Search for Meaning, by Viktor E. Frankl; The News: A User's Manual, by Alain de Botton; Mindware: Tools for Smart Thinking, by Richard E. Nisbett; The ABC of Relativity, by Bertrand Russell; The Psychopath Test, by Jon Ronson; The Path: What Chinese Philosophers Can Teach Us About the Good Life, by Michael Puett; A Brief History of Time, by Stephen Hawking; Messy: The Power of Disorder to Transform Our Lives, by Tim Harford; Big Data: A Revolution That Will Transform How We Live, Work, and Think, by Viktor Mayer-Schoenberger; Moneyball: The Art of Winning an Unfair Game, by Michael Lewis; The Survivors Club: The Secrets and Science That Could Save Your Life, by Ben Sherwood; Black Box Thinking, by Matthew Syed; Chaos: Making a New Science, by James Gleick; A Short History of Nearly Everything, by Bill Bryson; The Shallows: What the Internet Is Doing to Our Brains, by Nicholas Carr; Making Ideas Happen: Overcoming the Obstacles Between Vision and Reality, by Scott Belsky; The Enchiridion, by Epictetus; Goedel, Escher, Bach, by Douglas R. Hofstadter; What I Talk About When I Talk About Running, by Haruki Murakami; and Lateral Thinking, by Edward de Bono.

Wolfgang Engel's GPU Pro 360 Guide to Shadows gathers all the cutting-edge information from his previous seven GPU Pro volumes into a convenient single source anthology that covers various algorithms that are used to generate shadow data. This volume is complete with 15 articles by leading programmers that focus on achieving good visual results in rendering shadows. GPU Pro 360 Guide to Shadows is comprised of ready-to-use ideas and efficient procedures that can help solve many computer graphics programming challenges that may arise. Key Features: Presents tips & tricks on real-time rendering of special effects and visualization data on common consumer software platforms such as PCs, video consoles, mobile devices Covers specific challenges involved in creating games on various platforms Explores the latest developments in rapidly evolving field of real-time rendering Takes practical approach that helps graphics programmers solve their daily challenges

Algorithms and Theory of Computation Handbook, Second Edition: General Concepts and Techniques provides an up-to-date compendium of fundamental computer science topics and techniques. It also illustrates how the topics and techniques come together to deliver efficient solutions to important practical problems. Along with updating and revising many of the existing chapters, this second edition contains four new chapters that cover external memory and parameterized algorithms as well as computational number theory and algorithmic coding theory.

This best-selling handbook continues to help computer professionals and engineers find significant information on various algorithmic topics. The expert contributors clearly define the terminology, present basic results and techniques, and offer a number of current references to the in-depth literature. They also provide a glimpse of the major research issues concerning the relevant topics.

This is a timely, self-contained introduction to the rapidly expanding field of quantum information and computation that avoids detailed mathematical proofs wherever possible. The author uses a mixed exposition between a popular and technical approach, connecting the standard results of the field with more recent developments.
A complete but not highly technical textbook for students of physics, mathematics, and computer science.

This collection of different views on how digitalization is influencing various industrial sectors addresses essential topics like big data and analytics, fintech and insuretech, cloud and mobility technologies, disruption and entrepreneurship. The technological advances of the 21st century have been massively impacted by the digital upheaval: there is no future without digitalization. The sale of products and services has left the classical point of sale and now takes place on a variety of channels. Whether in the automotive industry, travel and traffic, in cities, or the financial industry - newly designed ecosystems are being created everywhere; data is being generated and analyzed in real time; and companies are competing for mobile access channels to customers in order to gain knowledge about their individual contexts and preferences. In turn, customers can now publicly share their opinions, experiences and knowledge as User Generated Content, allowing them to impact the market and empowering them to build or destroy trust.

This book teaches algebra and geometry. The authors dedicate chapters to the key issues of matrices, linear equations, matrix algorithms, vector spaces, lines, planes, second-order curves, and elliptic curves. The text is supported throughout with problems, and the authors have included source code in Python in the book. The book is suitable for advanced undergraduate and graduate students in computer science.

This powerful study tool is the best tutor you can have if you want top grades and thorough understanding of the fundamentals of computing with C++, the computing language taught at 83% of all colleges. This student-friendly study guide leads you step-by-step through the entire computer science course, giving you 420 problems with fully worked solutions and easy-to-follow examples for every new topic. You get complete explanations of data abstraction, recursion, Standard C++ container classes, searching, sorting algorithms, and other complex concepts, simplified and illustrated so theyre easy to grasp. You also get additional practice problems to solve on your own, working at your own speed. This superb study guide covers the entire course, from logic to libraries. If youre taking introduction to computer science, this book will be your best friend. Its perfect for independent study, too!

Our contemporary age is confronted by a profound contradiction: on the one hand, our lives as workers, consumers and citizens have become ever more monitored by new technologies. On the other, big business and finance become increasingly less regulated and controllable. What does this technocratic ideology and surveillance-heavy culture reveal about the deeper reality of modern society? Monitored investigates the history and implications of this modern accountability paradox. Peter Bloom reveals pervasive monitoring practices which mask how at its heart, the elite remains socially and ethically out of control. Challenging their exploitive 'accounting power', Bloom demands that the systems that administer our lives are oriented to social liberation and new ways of being in the world.

Spectral analysis is widely used to interpret time series collected in diverse areas. This book covers the statistical theory behind spectral analysis and provides data analysts with the tools needed to transition theory into practice. Actual time series from oceanography, metrology, atmospheric science and other areas are used in running examples throughout, to allow clear comparison of how the various methods address questions of interest. All major nonparametric and parametric spectral analysis techniques are discussed, with emphasis on the multitaper method, both in its original formulation involving Slepian tapers and in a popular alternative using sinusoidal tapers. The authors take a unified approach to quantifying the bandwidth of different nonparametric spectral estimates. An extensive set of exercises allows readers to test their understanding of theory and practical analysis. The time series used as examples and R language code for recreating the analyses of the series are available from the book's website.

The Untold Story of Everything Digital: Bright Boys, Revisited celebrates the 70th anniversary (1949-2019) of the world "going digital" for the very first time-real-time digital computing's genesis story. That genesis story is taken from the 2010 edition of Bright Boys: The Making of Information Technology, 1938-1958, and substantially expanded upon for this special, anniversary edition. Please join us for the incredible adventure that is The Untold Story of Everything Digital, when a band of misfit engineers, led by MIT's Jay Forrester and Bob Everett, birthed the digital revolution. The bright boys were the first to imagine an electronic landscape of computing machines and digital networks, and the first to blaze its high-tech trails.

Preparing for your SAP HANA 2.0 technology associate exam? Make the grade with this certification study guide! From installation and configuration to monitoring and troubleshooting, this guide will review the key technical and functional knowledge you need to pass with flying colors. Explore test methodology, key concepts for each area, and practice questions and answers. Your path to SAP HANA 2.0 certification begins here!Learn about the SAP HANA technology associate certification test structure and how to prepare. Review the key topics covered in each portion of the exam. Test your knowledge with practice questions and answers. Up to date for SPS 05 and exam C_HANATEC_16.