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Spaces of Teaching and Learning
by Robert A. Ellis Peter GoodyearThis integrated collection of perspectives on the spaces of teaching and learning uses ‘learning space’ to place educational practice in context. It considers the complex relationships involved in the design, management and use of contemporary learning spaces. It sheds light on some of the problems of connecting the characteristics of spaces to the practices and outcomes of teaching and learning. The contributions show how research into learning spaces can inform broader educational practices and how the practices of teaching, learning and design can inform research. The selection of chapters demonstrates the value of gathering together multiple sources of evidence, viewed through different epistemological lenses in order to push the field forward in a timely fashion. The book provides both a broad review of current practices as well as a deep-dive into particular educational and epistemological challenges that the various approaches adopted entail. Contrasts and commonalities between the different approaches emphasise the importance of developing a broad, robust evidence-base for practice in context. This is the inaugural book in the series Understanding Teaching-Learning Practice.
Space–Time Conservation Element and Solution Element Method: Advances and Applications in Engineering Sciences (Engineering Applications of Computational Methods #13)
by Chih-Yung Wen Yazhong Jiang Lisong ShiThis open access book introduces the fundamentals of the space–time conservation element and solution element (CESE) method, which is a novel numerical approach for solving equations of physical conservation laws. It highlights the recent progress to establish various improved CESE schemes and its engineering applications. With attractive accuracy, efficiency, and robustness, the CESE method is particularly suitable for solving time-dependent nonlinear hyperbolic systems involving dynamical evolutions of waves and discontinuities. Therefore, it has been applied to a wide spectrum of problems, e.g., aerodynamics, aeroacoustics, magnetohydrodynamics, multi-material flows, and detonations. This book contains algorithm analysis, numerical examples, as well as demonstration codes. This book is intended for graduate students and researchers who are interested in the fields such as computational fluid dynamics (CFD), mechanical engineering, and numerical computation.
Spam: A Shadow History of the Internet (Infrastructures)
by Finn BruntonWhat spam is, how it works, and how it has shaped online communities and the Internet itself.The vast majority of all email sent every day is spam, a variety of idiosyncratically spelled requests to provide account information, invitations to spend money on dubious products, and pleas to send cash overseas. Most of it is caught by filters before ever reaching an in-box. Where does it come from? As Finn Brunton explains in Spam, it is produced and shaped by many different populations around the world: programmers, con artists, bots and their botmasters, pharmaceutical merchants, marketers, identity thieves, crooked bankers and their victims, cops, lawyers, network security professionals, vigilantes, and hackers. Every time we go online, we participate in the system of spam, with choices, refusals, and purchases the consequences of which we may not understand.This is a book about what spam is, how it works, and what it means. Brunton provides a cultural history that stretches from pranks on early computer networks to the construction of a global criminal infrastructure. The history of spam, Brunton shows us, is a shadow history of the Internet itself, with spam emerging as the mirror image of the online communities it targets. Brunton traces spam through three epochs: the 1970s to 1995, and the early, noncommercial computer networks that became the Internet; 1995 to 2003, with the dot-com boom, the rise of spam's entrepreneurs, and the first efforts at regulating spam; and 2003 to the present, with the war of algorithms—spam versus anti-spam. Spam shows us how technologies, from email to search engines, are transformed by unintended consequences and adaptations, and how online communities develop and invent governance for themselves.
Spam Kings: The Real Story Behind the High-Rolling Hucksters Pushing Porn, Pills, and %*@)# Enlargements
by Brian S McWilliams"People are stupid, Davis Wolfgang Hawke thought as he stared at the nearly empty box of Swastika pendants on his desk." So begins Spam Kings, an investigative look into the shady world of email spammers and the people trying to stop them.This compelling exposé explores the shadowy world of the people responsible for today’s junk-email epidemic. Investigative journalist Brian McWilliams delivers a fascinating account of the cat-and-mouse game played by spam entrepreneurs in search of easy fortunes and anti-spam activists.McWilliams chronicles the activities of several spam kings, including Hawke, a notorious Jewish-born neo-Nazi leader. You’ll follow this 20-year-old’s rise in the trade, where he became a major player in the lucrative penis pill market—a business that would make him a millionaire and the target of lawsuits. You’ll also meet cyber-vigilantes, such as Susan Gunn, who have taken up the fight against spammers like Hawke.Explore the sleazy spammer business practices, the surprising new partnership between spammers and computer hackers, and the rise of a new breed of computer viruses designed to turn the PCs of innocent bystanders into secret spam factories.
Spam Nation: The Inside Story of Organized Cybercrime—from Global Epidemic to Your Front Door
by Brian KrebsA New York Times bestseller and winner of a 2015 Prose Award!There is a threat lurking online. A secret war with the power to destroy your finances, steal your personal data, and endanger your life.In Spam Nation, investigative journalist and cybersecurity expert Brian Krebs unmasks the criminal masterminds driving some of the biggest spam and hacker operations targeting Americans and their bank accounts. Tracing the rise, fall, and alarming resurrection of the digital mafia behind the two largest spam pharmacies—and countless viruses, phishing, and spyware attacks—he delivers the first definitive narrative of the global spam problem and its threat to consumers everywhere.Blending cutting-edge research, investigative reporting, and firsthand interviews, this terrifying true story reveals how we unwittingly invite these digital thieves into our lives every day. From unassuming computer programmers right next door to digital mobsters like "Cosma"—who unleashed a massive malware attack that has stolen thousands of Americans' logins and passwords—Krebs uncovers the shocking lengths to which these people will go to profit from our data and our wallets.Not only are hundreds of thousands of Americans exposing themselves to fraud and dangerously toxic products from rogue online pharmacies, but even those who never open junk messages are at risk. As Krebs notes, spammers can—and do—hack into accounts through these emails, harvest personal information like usernames and passwords, and sell them on the digital black market. The fallout from this global epidemic doesn't just cost consumers and companies billions, it costs lives too.Fast-paced and utterly gripping, Spam Nation ultimately proposes concrete solutions for protecting ourselves online and stemming this tidal wave of cybercrime—before it's too late."Krebs's talent for exposing the weaknesses in online security has earned him respect in the IT business and loathing among cybercriminals… His track record of scoops...has helped him become the rare blogger who supports himself on the strength of his reputation for hard-nosed reporting." —Bloomberg Businessweek
SpamAssassin: A practical guide to integration and configuration
by Alistair McdonaldWritten specifically for busy network and system administrators, the book is a detailed and practical guide to implementing the right antispam solution for your network and your business requirements. You'll go from a detailed walk through of initial set up, to advanced configuration options like Bayesian filtering, listing, rewriting, and rules. The book shows how to optimize SpamAssassin for all major mail servers and clients. If you are a network or system administrator and you're either using or evaluating SpamAssassin, this book will increase your understanding and transform your productivity.
SpamAssassin
by Alan SchwartzSys admins can field scores of complaints and spend months testing software suites that turn out to be too aggressive, too passive, or too complicated to setup only to discover that SpamAssassin (SA), the leading open source spam-fighting tool, is free, flexible, powerful, highly-regarded, and remarkably effective. The drawback? Until now, it was SpamAssassin's lack of published documentation. This clear, concise new guide provides the expertise you need to take back your inbox. "Detailed, accurate and informative--recommended for spam-filtering beginners and experts alike." --Justin Mason, SpamAssassin development team
The Spanish Armada: A Ladybird Expert Book (The Ladybird Expert Series #30)
by Sam WillisPart of the ALL-NEW LADYBIRD EXPERT SERIES.____________Why did the Spanish launch their Armada on England?How did Francis Drake counter the Spanish threat?And why were so many ships lost at sea?In 1585 Spain was the most POWERFUL Empire in the known world.As tensions between PROTESTANT England and CATHOLIC Spain rose . . . SPAIN decided to INVADE ENGLAND. And launched the SPANISH ARMADA This raises the question: how did England manage to overthrow the Spanish invasion? Was it luck or judgement? Discover the answers and more inside Sam Willis's Ladybird Expert - The Spanish Armada, the thrilling and accessible account that explains what happened, who the key figures were and the tactics, triumphs and failures on both sides . . .
The Spanish Model for Smart Tourism Destination Management: A Methodological Approach (Tourism, Hospitality & Event Management)
by Lidia Andrades Carlos Romero-Dexeus Enrique Martínez-MarínThis is an open access handbook that guides destinations on their journey to becoming Smart Tourism Destinations (STDs). Developed by SEGITTUR, a distinguished Spanish State company, and aligned with academia represented by Professor Lidia Andrades, who has brought together recognized international academics with SEGITTUR experts in the field of tourism management to write this groundbreaking book, it offers practical insights and strategies for success. Explore the characteristics and implications of smart destinations, across the five dimensions which structure them: destination governance, accessibility, technology, innovation and sustainability, navigate the transition from traditional tourism management to the innovative smart managerial paradigm, and overcome challenges encountered during the transformative process. Equipping destination managers with essential tools and strategies, this handbook showcases real-life examples of Spanish destinations embracing the smart tourism paradigm. Drawing on SEGITTUR's proven methodology, it provides precise guidance, checklists, and expert recommendations for effective implementation. An invaluable resource for destination managers, tourism professionals, and researchers, it unlocks the full potential of smart tourism destinations.
Spanning Trees and Optimization Problems (Discrete Mathematics and Its Applications)
by Bang Ye Wu Kun-Mao ChaoThe design of approximation algorithms for spanning tree problems has become an exciting and important area of theoretical computer science and also plays a significant role in emerging fields such as biological sequence alignments and evolutionary tree construction. While work in this field remains quite active, the time has come to collect under
Spark: Big Data Processing Made Simple
by Bill Chambers Matei ZahariaLearn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals.Youâ??ll explore the basic operations and common functions of Sparkâ??s structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Sparkâ??s scalable machine-learning library.Get a gentle overview of big data and SparkLearn about DataFrames, SQL, and Datasetsâ??Sparkâ??s core APIsâ??through worked examplesDive into Sparkâ??s low-level APIs, RDDs, and execution of SQL and DataFramesUnderstand how Spark runs on a clusterDebug, monitor, and tune Spark clusters and applicationsLearn the power of Structured Streaming, Sparkâ??s stream-processing engineLearn how you can apply MLlib to a variety of problems, including classification or recommendation
Spark: Big Data Cluster Computing in Production
by Ilya Ganelin Ema Orhian Kai Sasaki Brennon YorkProduction-targeted Spark guidance with real-world use cases Spark: Big Data Cluster Computing in Production goes beyond general Spark overviews to provide targeted guidance toward using lightning-fast big-data clustering in production. Written by an expert team well-known in the big data community, this book walks you through the challenges in moving from proof-of-concept or demo Spark applications to live Spark in production. Real use cases provide deep insight into common problems, limitations, challenges, and opportunities, while expert tips and tricks help you get the most out of Spark performance. Coverage includes Spark SQL, Tachyon, Kerberos, ML Lib, YARN, and Mesos, with clear, actionable guidance on resource scheduling, db connectors, streaming, security, and much more. Spark has become the tool of choice for many Big Data problems, with more active contributors than any other Apache Software project. General introductory books abound, but this book is the first to provide deep insight and real-world advice on using Spark in production. Specific guidance, expert tips, and invaluable foresight make this guide an incredibly useful resource for real production settings. Review Spark hardware requirements and estimate cluster size Gain insight from real-world production use cases Tighten security, schedule resources, and fine-tune performance Overcome common problems encountered using Spark in production Spark works with other big data tools including MapReduce and Hadoop, and uses languages you already know like Java, Scala, Python, and R. Lightning speed makes Spark too good to pass up, but understanding limitations and challenges in advance goes a long way toward easing actual production implementation. Spark: Big Data Cluster Computing in Production tells you everything you need to know, with real-world production insight and expert guidance, tips, and tricks.
Spark Cookbook
by Rishi YadavIf you are a data engineer, an application developer, or a data scientist who would like to leverage the power of Apache Spark to get better insights from big data, then this is the book for you.
Spark Cookbook
by Rishi YadavBy introducing in-memory persistent storage, Apache Spark eliminates the need to store intermediate data in filesystems, thereby increasing processing speed by up to 100 times. This book will focus on how to analyze large and complex sets of data. Starting with installing and configuring Apache Spark with various cluster managers, you will cover setting up development environments. You will then cover various recipes to perform interactive queries using Spark SQL and real-time streaming with various sources such as Twitter Stream and Apache Kafka. You will then focus on machine learning, including supervised learning, unsupervised learning, and recommendation engine algorithms. After mastering graph processing using GraphX, you will cover various recipes for cluster optimization and troubleshooting.
Spark for Data Science
by Bikramaditya Singhal Srinivas DuvvuriAnalyze your data and delve deep into the world of machine learning with the latest Spark version, 2.0 About This Book * Perform data analysis and build predictive models on huge datasets that leverage Apache Spark * Learn to integrate data science algorithms and techniques with the fast and scalable computing features of Spark to address big data challenges * Work through practical examples on real-world problems with sample code snippets Who This Book Is For This book is for anyone who wants to leverage Apache Spark for data science and machine learning. If you are a technologist who wants to expand your knowledge to perform data science operations in Spark, or a data scientist who wants to understand how algorithms are implemented in Spark, or a newbie with minimal development experience who wants to learn about Big Data Analytics, this book is for you! What You Will Learn * Consolidate, clean, and transform your data acquired from various data sources * Perform statistical analysis of data to find hidden insights * Explore graphical techniques to see what your data looks like * Use machine learning techniques to build predictive models * Build scalable data products and solutions * Start programming using the RDD, DataFrame and Dataset APIs * Become an expert by improving your data analytical skills In Detail This is the era of Big Data. The words 'Big Data' implies big innovation and enables a competitive advantage for businesses. Apache Spark was designed to perform Big Data analytics at scale, and so Spark is equipped with the necessary algorithms and supports multiple programming languages. Whether you are a technologist, a data scientist, or a beginner to Big Data analytics, this book will provide you with all the skills necessary to perform statistical data analysis, data visualization, predictive modeling, and build scalable data products or solutions using Python, Scala, and R. With ample case studies and real-world examples, Spark for Data Science will help you ensure the successful execution of your data science projects. Style and approach This book takes a step-by-step approach to statistical analysis and machine learning, and is explained in a conversational and easy-to-follow style. Each topic is explained sequentially with a focus on the fundamentals as well as the advanced concepts of algorithms and techniques. Real-world examples with sample code snippets are also included.
Spark for Data Science Cookbook
by Padma Priya ChitturiThis book is for novice and intermediate level data scientists and data analysts who want to solve data science problems using a distributed computing framework such as Spark. You are expected to have knowledge on statistics, data science tools such as R and Pandas, and an understanding of distributed systems, as well as some exposure to Hadoop.
Spark for Python Developers
by Amit NandiA concise guide to implementing Spark Big Data analytics for Python developers, and building a real-time and insightful trend tracker data intensive app About This Book * Set up real-time streaming and batch data intensive infrastructure using Spark and Python * Deliver insightful visualizations in a web app using Spark (PySpark) * Inject live data using Spark Streaming with real-time events Who This Book Is For This book is for data scientists and software developers with a focus on Python who want to work with the Spark engine, and it will also benefit Enterprise Architects. All you need to have is a good background of Python and an inclination to work with Spark. What You Will Learn * Create a Python development environment powered by Spark (PySpark), Blaze, and Bookeh * Build a real-time trend tracker data intensive app * Visualize the trends and insights gained from data using Bookeh * Generate insights from data using machine learning through Spark MLLIB * Juggle with data using Blaze * Create training data sets and train the Machine Learning models * Test the machine learning models on test datasets * Deploy the machine learning algorithms and models and scale it for real-time events In Detail Looking for a cluster computing system that provides high-level APIs? Apache Spark is your answer--an open source, fast, and general purpose cluster computing system. Spark's multi-stage memory primitives provide performance up to 100 times faster than Hadoop, and it is also well-suited for machine learning algorithms. Are you a Python developer inclined to work with Spark engine? If so, this book will be your companion as you create data-intensive app using Spark as a processing engine, Python visualization libraries, and web frameworks such as Flask. To begin with, you will learn the most effective way to install the Python development environment powered by Spark, Blaze, and Bookeh. You will then find out how to connect with data stores such as MySQL, MongoDB, Cassandra, and Hadoop. You'll expand your skills throughout, getting familiarized with the various data sources (Github, Twitter, Meetup, and Blogs), their data structures, and solutions to effectively tackle complexities. You'll explore datasets using iPython Notebook and will discover how to optimize the data models and pipeline. Finally, you'll get to know how to create training datasets and train the machine learning models. By the end of the book, you will have created a real-time and insightful trend tracker data-intensive app with Spark. Style and approach This is a comprehensive guide packed with easy-to-follow examples that will take your skills to the next level and will get you up and running with Spark.
Spark GraphX in Action
by Michael Malak Robin EastSummarySpark GraphX in Action starts out with an overview of Apache Spark and the GraphX graph processing API. This example-based tutorial then teaches you how to configure GraphX and how to use it interactively. Along the way, you'll collect practical techniques for enhancing applications and applying machine learning algorithms to graph data.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyGraphX is a powerful graph processing API for the Apache Spark analytics engine that lets you draw insights from large datasets. GraphX gives you unprecedented speed and capacity for running massively parallel and machine learning algorithms.About the BookSpark GraphX in Action begins with the big picture of what graphs can be used for. This example-based tutorial teaches you how to use GraphX interactively. You'll start with a crystal-clear introduction to building big data graphs from regular data, and then explore the problems and possibilities of implementing graph algorithms and architecting graph processing pipelines. Along the way, you'll collect practical techniques for enhancing applications and applying machine learning algorithms to graph data.What's InsideUnderstanding graph technologyUsing the GraphX APIDeveloping algorithms for big graphsMachine learning with graphsGraph visualizationAbout the ReaderReaders should be comfortable writing code. Experience with Apache Spark and Scala is not required.About the AuthorsMichael Malak has worked on Spark applications for Fortune 500 companies since early 2013. Robin East has worked as a consultant to large organizations for over 15 years and is a data scientist at Worldpay.Table of ContentsPART 1 SPARK AND GRAPHSTwo important technologies: Spark and graphsGraphX quick startSome fundamentalsPART 2 CONNECTING VERTICESGraphX BasicsBuilt-in algorithmsOther useful graph algorithmsMachine learningPART 3 OVER THE ARCThe missing algorithmsPerformance and monitoringOther languages and tools
Spark in Action
by Marko Bonaci Petar ZecevicSummarySpark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark. Fully updated for Spark 2.0.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyBig data systems distribute datasets across clusters of machines, making it a challenge to efficiently query, stream, and interpret them. Spark can help. It is a processing system designed specifically for distributed data. It provides easy-to-use interfaces, along with the performance you need for production-quality analytics and machine learning. Spark 2 also adds improved programming APIs, better performance, and countless other upgrades.About the BookSpark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark. You'll get comfortable with the Spark CLI as you work through a few introductory examples. Then, you'll start programming Spark using its core APIs. Along the way, you'll work with structured data using Spark SQL, process near-real-time streaming data, apply machine learning algorithms, and munge graph data using Spark GraphX. For a zero-effort startup, you can download the preconfigured virtual machine ready for you to try the book's code. What's InsideUpdated for Spark 2.0Real-life case studiesSpark DevOps with DockerExamples in Scala, and online in Java and PythonAbout the ReaderWritten for experienced programmers with some background in big data or machine learning. About the AuthorsPetar Zečević and Marko Bonaći are seasoned developers heavily involved in the Spark community.Table of ContentsPART 1 - FIRST STEPSIntroduction to Apache Spark Spark fundamentals Writing Spark applicationsThe Spark API in depth PART 2 - MEET THE SPARK FAMILY Sparkling queries with Spark SQL Ingesting data with Spark Streaming Getting smart with MLlib ML: classification and clustering Connecting the dots with GraphX PART 3 - SPARK OPSRunning Spark Running on a Spark standalone cluster Running on YARN and MesosPART 4 - BRINGING IT TOGETHERCase study: real-time dashboard Deep learning on Spark with H2O
Spark in Action: Covers Apache Spark 3 with Examples in Java, Python, and Scala
by Jean-Georges PerrinSummary The Spark distributed data processing platform provides an easy-to-implement tool for ingesting, streaming, and processing data from any source. In Spark in Action, Second Edition, you&’ll learn to take advantage of Spark&’s core features and incredible processing speed, with applications including real-time computation, delayed evaluation, and machine learning. Spark skills are a hot commodity in enterprises worldwide, and with Spark&’s powerful and flexible Java APIs, you can reap all the benefits without first learning Scala or Hadoop. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Analyzing enterprise data starts by reading, filtering, and merging files and streams from many sources. The Spark data processing engine handles this varied volume like a champ, delivering speeds 100 times faster than Hadoop systems. Thanks to SQL support, an intuitive interface, and a straightforward multilanguage API, you can use Spark without learning a complex new ecosystem. About the book Spark in Action, Second Edition, teaches you to create end-to-end analytics applications. In this entirely new book, you&’ll learn from interesting Java-based examples, including a complete data pipeline for processing NASA satellite data. And you&’ll discover Java, Python, and Scala code samples hosted on GitHub that you can explore and adapt, plus appendixes that give you a cheat sheet for installing tools and understanding Spark-specific terms. What's inside Writing Spark applications in Java Spark application architecture Ingestion through files, databases, streaming, and Elasticsearch Querying distributed datasets with Spark SQL About the reader This book does not assume previous experience with Spark, Scala, or Hadoop. About the author Jean-Georges Perrin is an experienced data and software architect. He is France&’s first IBM Champion and has been honored for 12 consecutive years. Table of Contents PART 1 - THE THEORY CRIPPLED BY AWESOME EXAMPLES 1 So, what is Spark, anyway? 2 Architecture and flow 3 The majestic role of the dataframe 4 Fundamentally lazy 5 Building a simple app for deployment 6 Deploying your simple app PART 2 - INGESTION 7 Ingestion from files 8 Ingestion from databases 9 Advanced ingestion: finding data sources and building your own 10 Ingestion through structured streaming PART 3 - TRANSFORMING YOUR DATA 11 Working with SQL 12 Transforming your data 13 Transforming entire documents 14 Extending transformations with user-defined functions 15 Aggregating your data PART 4 - GOING FURTHER 16 Cache and checkpoint: Enhancing Spark&’s performances 17 Exporting data and building full data pipelines 18 Exploring deployment
The SparkFun Guide to Processing
by Derek RunbergProcessing is a free, beginner-friendly programming language designed to help non-programmers create interactive art with code.The SparkFun Guide to Processing, the first in the SparkFun Electronics series, will show you how to craft digital artwork and even combine that artwork with hardware so that it reacts to the world around you. Start with the basics of programming and animation as you draw colorful shapes and make them bounce around the screen. Then move on to a series of hands-on, step-by-step projects that will show you how to:–Make detailed pixel art and scale it to epic proportions–Write a maze game and build a MaKey MaKey controller with fruit buttons–Play, record, and sample audio to create your own soundboard–Fetch weather data from the Web and build a custom weather dashboard–Create visualizations that change based on sound, light, and temperature readingsWith a little imagination and Processing as your paintbrush, you’ll be on your way to coding your own gallery of digital art in no time! Put on your artist’s hat, and begin your DIY journey by learning some basic programming and making your first masterpiece with The SparkFun Guide to Processing.The code in this book is compatible with Processing 2 and Processing 3.
Sparrow iOS Game Framework Beginner’s Guide
by Johannes SteinAn easy-to-follow guide full of descriptive step-by-step procedures on how to develop a game for iOS. With each topic, a new challenge will be tackled to get a deeper knowledge of the Sparrow game framework and gain the skills to develop a complete mobile experience. This book is aimed at those who have always wanted to create their own games for iOS devices. Perhaps you've already dabbled in game development and want to know how to develop games for the Apple App Store, or maybe you have developed Objective-C apps in the past but you are new to game development. In either case, this book will help with descriptive examples and teach you to develop a game throughout its course. Some experience in Objective-C and a basic understanding of object-oriented programming are required.
Sparse Estimation with Math and R: 100 Exercises for Building Logic
by Joe SuzukiThe most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than knowledge and experience. This textbook approaches the essence of sparse estimation by considering math problems and building R programs. Each chapter introduces the notion of sparsity and provides procedures followed by mathematical derivations and source programs with examples of execution. To maximize readers’ insights into sparsity, mathematical proofs are presented for almost all propositions, and programs are described without depending on any packages. The book is carefully organized to provide the solutions to the exercises in each chapter so that readers can solve the total of 100 exercises by simply following the contents of each chapter.This textbook is suitable for an undergraduate or graduate course consisting of about 15 lectures (90 mins each). Written in an easy-to-follow and self-contained style, this book will also be perfect material for independent learning by data scientists, machine learning engineers, and researchers interested in linear regression, generalized linear lasso, group lasso, fused lasso, graphical models, matrix decomposition, and multivariate analysis.This book is one of a series of textbooks in machine learning by the same author. Other titles are: - Statistical Learning with Math and R (https://www.springer.com/gp/book/9789811575679) - Statistical Learning with Math and Python (https://www.springer.com/gp/book/9789811578762) - Sparse Estimation with Math and Python
Sparse Grids and Applications - Miami 2016 (Lecture Notes in Computational Science and Engineering #123)
by Jochen Garcke Dirk Pflüger Clayton G. Webster Guannan ZhangSparse grids are a popular tool for the numerical treatment of high-dimensional problems. Where classical numerical discretization schemes fail in more than three or four dimensions, sparse grids, in their different flavors, are frequently the method of choice. This volume of LNCSE presents selected papers from the proceedings of the fourth workshop on sparse grids and applications, and demonstrates once again the importance of this numerical discretization scheme. The articles present recent advances in the numerical analysis of sparse grids in connection with a range of applications including computational chemistry, computational fluid dynamics, and big data analytics, to name but a few.
Sparse Grids and Applications - Munich 2018 (Lecture Notes in Computational Science and Engineering #144)
by Hans-Joachim Bungartz Jochen Garcke Dirk PflügerSparse grids are a popular tool for the numerical treatment of high-dimensional problems. Where classical numerical discretization schemes fail in more than three or four dimensions, sparse grids, in their different flavors, are frequently the method of choice.This volume of LNCSE presents selected papers from the proceedings of the fifth workshop on sparse grids and applications, and demonstrates once again the importance of this numerical discretization scheme. The articles present recent advances in the numerical analysis of sparse grids in connection with a range of applications including uncertainty quantification, plasma physics simulations, and computational chemistry, to name but a few.