Big Data and High-Performance Computing: Methodologies and Applications studies novel efficient analytical techniques to speed up data processing, emerging high-performance architectures for data-intensive applications, and cutting-edge applications in a variety of domains, including machine learning, life science, neural networks, and neuromorphic engineering.
Natural language processing (NLP) issues are covered in many books and courses using toy use cases and well-defined datasets. However, if you want to construct, improve, and expand NLP systems in a commercial environment and customize them for specific industrial verticals, this is your manual. Data scientists and software engineers will learn how to maneuver through the tangle of choices presented at each stage of the journey.
Comprehensive covering of database management system foundations is provided in this book. In it, Relational Database Management System Concepts are explained in great detail. There are numerous examples with solutions and review questions with answers. This book is intended for readers who want to get a deeper grasp of relational data modeling, including its goals, characteristics, and standards.
Database system principles provides the foundational ideas of database administration in an easy-to-understand way designed to let students start using databases as soon as possible. The only prerequisites are knowledge with high-level programming languages, basic data structures, and computer architecture.
This book discusses data structure algorithms in a way that is independent of both machines and languages. It is intended to serve as a textbook or supplemental material for efficient self-study and takes an introductory approach to the subject matter with lots of examples and graphics. The presentation of algorithms in pseudocode and a thorough description of AVL search trees, m-way search trees, and B trees are special characteristics.
The TCP/IP protocol suite is used to teach networking fundamentals in Behrouz A. Forouzan's Data Communications and Networking, 6th Edition. The book's 13 chapters, 6 appendices, and comprehensive pedagogy, which includes practice sets, real-world applications, and visual representations, will make data communications and networking easier for students to understand.
This best-selling text from Pearson provides a clear and thorough examination of the whole data and computer communications area with a focus on the most recent technology and a practical modular approach.
This version of Forouzan's Data Communications and Networking is being presented with great pleasure. It has been created especially to address the needs of computer network students.
This book has been giving students the knowledge they require to comprehend and use multivariate data analysis for more than 30 years. The eighth edition of Multivariate Data Analysis offers an updated viewpoint on the analysis of various forms of data in addition to offering some fresh viewpoints and cutting-edge analytical approaches.
Welcome to the dirty little secret of data science: messy real-world data. Before they can truly use the data for anything useful, data scientists must first spend a significant amount of time pretending to be software developers and building code to clean it up. Even though this is a necessary evil, we can still benefit from it.
An introduction to data mining techniques and models, such as association rules, clustering, neural networks, logistic regression, and multivariate analysis, is provided by this revised second edition. The authors tackle data mining techniques and models using a single, cohesive "white box" approach. With the use of tiny data sets, this method aims to guide readers through the subtleties and workings of the different approaches, giving them a better understanding of the inner workings of the method they are reviewing.
Scientists, engineers, and businesspeople have access to a wealth of new resources thanks to the quick development and integration of databases. These resources can be studied to find patterns that have commercial value, optimize industrial processes, and lead to scientific breakthroughs. Researchers and practitioners have developed novel techniques specifically aimed at huge data mining challenges in addition to adopting well-established algorithms from databases, machine learning, neural networks, and statistics to carry out these massive data mining projects.
Market: For computer science and information technology/MCA undergraduate courses The author gives the reader a thorough understanding of data mining concepts and algorithms in this book. The book maintains a data base perspective throughout, giving students a targeted study of data types, algorithms, data structures, and algorithm and space complexity. Additionally, it highlights how data mining principles are applied in practical applications with sizable database components.
Elmasri and Navathe's seventh edition of their best-selling book on database systems is released by Pearson. The essential ideas needed to build, use, and implement database systems and database applications are introduced in this extensively redesigned edition. The foundations of database modeling and design, the languages and models offered by database management systems, and database system implementation strategies are the main points of emphasis in our talk.The book can be used as a reference work and as a textbook for junior, senior, or graduate-level database systems courses lasting one or two semesters. The main objective is to describe the most significant features of database systems, applications, and associated technologies in a comprehensive and current manner.
Big Data Science Fundamentals provides technologists and business people with a thorough, approachable, and current understanding of big data. Key Big Data concepts, theory, terminology, technologies, and essential analysis/analytics approaches are introduced by renowned corporate technology expert Thomas Erl. Everything is rationally arranged, communicated in simple English, and backed by clear diagrams and case study examples. Qualities: covers principles, theory, vocabulary, technology, important analysis/analytics methodologies, and more in a vendor-neutral manner. Hundreds of photos, illustrations, and actual case studies are used to shed light on both basic and advanced topics. explains the connections between business intelligence systems, analytical capabilities, and current enterprise technologies with big data. logically ordered, consistent, clear, and current.
Section 1: Comprehending Big Data 1: The Big Data Story 3: Artificial Intelligence, Machine Learning, and Big Data 21 3 What makes large data valuable? 33 Four (large) data analytics use cases 5 Knowing the environment of big data 65 Part 2: Using the big data ecosystem to your company's advantage 81 6 How to use big data to inform your approach 83 7 Developing your big data and data science 101 plan 8 Putting machine learning, analytics, and data science into practice 121 contents
In keeping with the philosophy of Schaum's Outlines, this book's current edition covers the fundamentals of data structures and augments it with worked-out examples and programming challenges. The well-known and iconic work is back, featuring updated pedagogy and programming problems that give students a better grasp of the material in a practical setting.
Every J2EE application that is significant to business is covered in portions of the book. The J2EE architecture, databasing, and Web services are first explained. Best practices for dealing with Java Servlets, JSPs, EJBs, and JDBCs are covered in the book, along with methods for building components with these technologies. It also includes a crucial section on how to develop the Java Message Service and Java Server API, which will aid the reader in assimilating and utilizing J2EE's security features. Additionally, it includes a section on Web Service Description Language (WSDL) implementation. It is a cutting-edge manual that is extensively read and used in the business, and it is advised for developers working on Web and direct J2EE applications.
For graduates in communications and electronics, data structures are a crucial component of their coursework. For these students, Data Structures with C (Schaum's Outline Series) is an essential resource that aids in understanding the ideas and concepts underlying data structures. The book covers data structures in great detail and comprehensively. The book's many innovative instructional elements make it easier for students to understand the material.
An introduction to data mining techniques and models is given in this book. These techniques and models include association rules, clustering, K-nearest neighbor, statistical inference, neural networks, multivariate analysis, and linear and logistic regression. It offers a cohesive strategy built on the CRISP methodology, which stands for organizational modeling-based strategic risk assessment.
Businesses have spent a lot of money constructing data warehouses in order to collect enormous volumes of client data. Making smarter business judgments comes from "mining" this information gold mine, or gaining access to the data within. Because Berry and Linoff so clearly show useful strategies that have genuine benefits for increased marketing and sales, readers and reviewers adored their debut book, Data Mining strategies. From then, Mastering Data Mining takes off. Assuming readers are familiar with the fundamental methods discussed in the first book, the writers concentrate on the most effective ways to apply these methods to actual business scenarios. Over the course of roughly 20 scenarios, they begin with the most basic applications and progress to the most potent and complex examples.
The Data Warehouse Toolkit
The book demonstrates to readers how to use open source and Microsoft technology to set up their company for big data. The book teaches readers how to use Microsoft HDInsight Service, the company's latest Big Data solution, to store, manage, analyze, and share Big Data across the enterprise.
A useful manual for data mining with Excel and SQL Data Analysis In order to accomplish advanced data analysis without the need for complicated and costly data mining technologies, Using SQL and Excel, 2nd Edition demonstrates how to make the most of the two most widely used tools for data query and analysis: SQL and Excel. This book, written by a world-renowned authority on business data mining, teaches you how to glean valuable business insights from relational databases. Before going into the "where" and "why" of each study, you will learn the basic approaches. After that, you will learn how to use SQL and Excel to create and carry out these analyses.
This concise and approachable introduction to database systems, written by renowned computer scientists, concentrates on database architecture and usage. The authors leave implementation for later courses and give thorough coverage of databases from the perspectives of the database designer, user, and application programmer. This publication is the first on database systems, including subjects like 3-tier designs, data cubes, XML, XPATH, XQuery, XSLT, extended relational algebra, UML, and algorithms for manipulating dependencies in relations.
A premier introduction to database systems is produced by providing concise explanations of theory and design, extensive treatment of models and actual systems, and a current introduction to contemporary database technology. Students will get more opportunity to practice the principles of design and implementation with new challenges and a revised lab manual. Additional real-world examples provide interesting and useful demonstrations of database principles. The Fifth Edition adds a new chapter on online script programming for databases while keeping up its coverage of the most widely used database subjects, such as SQL, security, and data mining.
An introduction to the concepts and methods of information extraction from a business-minded viewpoint is given in this data mining primer. Thirteen data mining lessons help to establish and then improve a fundamental understanding of the subject of data mining principles. After finishing these lessons, students will be proficient in data mining. Students studying information technology, MIS, and computer science should read this book.
Information Organizations Students and experts may construct abstract structures and structure their thoughts to meet varied demands by using C, which combines a basic course on data structures with all of the programming approaches. This book uses C as the fundamental programming language to expound on common data structures. It's intended for use in a one-semester Data Structures course.
This textbook has been giving students the knowledge they need to comprehend and use multivariate data analysis for more than 30 years. For the non-statistician, Hair et al. offers an applications-focused introduction to multivariate analysis. The manual helps students comprehend and apply the findings of certain statistical procedures by distilling complex statistical research into basic ideas. The chapters are now much more simply organized in this seventh iteration. Structural equation modeling has had new chapters introduced, and all portions have been revised to take into account advancements in mathematical methodologies, technology, and capabilities.
Businesses can utilize data warehouses to analyze and exploit the information contained in their computerized systems to achieve a competitive edge. In-depth instructions and methods for utilizing open-systems data warehouses to give decision support solutions are provided in Data Warehousing in the Real World. This book, written by practitioners for practitioners, provides a detailed description of every step in the implementation process.
A thorough introduction to the vast area of database systems is given in An Introduction to Database Systems. It provides a strong foundation in database technology and offers some insight into the direction that the industry is likely to take in the future. To keep up with the latest advancements in database systems, this version has been updated and revised; yet, the primary focus still lies on comprehension and insight rather than merely formalisms.
Finding hidden information as well as odd patterns and laws in huge databases is the focus of data mining. For instance, more effective internal performance and more precisely focused marketing are only two ways it may benefit companies greatly. This book is the first to provide a thorough introduction to data mining. Its goal is to give you the necessary knowledge and pointers to enable you to set up a data mining environment wisely.
This is the official guide to using Microsoft Master Data Services, the Master Data Management tool that comes with SQL Server 2012, written by the technologists who created the program.
Buchanan, Mc Graw Hill India, Finite Element Analysis (Special Indian Edition) (Schaum'S Outline Series)
A thorough study guide for certification exams is the OCA Oracle Database SQL Certified Expert Exam Guide. With the help of this book, candidates can get ready for their Oracle Certified Associate SQL Certified Expert exam. To help students prepare effectively, the book includes difficult practice problems, exercises, and other drills. The book is broken up into eighteen chapters that cover each important topic related to SQL in detail. Data manipulation as well as the creation and administration of tables are covered in several chapters. The chapters cover a variety of data manipulation strategies as well as additional techniques for organizing and sorting data. Reporting and presenting data from different tables are discussed. The author has also covered managing and creating schema objects. Using set operators, working with big data sets, retrieving information hierarchically, regular expression support, and managing user access are all covered in separate sections.
An Overview of Data Structures and Their Applications
For web developers looking to improve their websites with database interaction, PHP and MySQL are helpful tools. It is also beneficial to those of you who wish to begin creating websites that rely significantly on data. The book walks you through an overview of PHP and MySQL, going into great detail about how to do tasks, monitor development, create forms, put together tables, manage data, link databases, create user accounts, run forums, and much more.
This book covers database fundamentals and leads users through the process of developing and creating databases. It also includes exercises and problems at the conclusion of each chapter to promote practical learning.
Physical oceanography is the study of the physical features and functions of the ocean, especially the motions and properties of its waters. Physical oceanography is one of the many sub-domains that make up oceanography. The others are oceanography in the fields of geology, chemistry, and biology. Physical Oceanography is a scientific discipline that studies the physical processes in the ocean, the interaction between the ocean and the atmosphere, and the ocean's role in Earth's climate and ecosystems. Some of the major themes in physical oceanography are the dynamics of ocean currents on spatial scales ranging from centimeters to global, the variability of these currents on time-scales from seconds to millennia, ocean wave phenomena, the distribution of heat and salt and other water properties and their transport by currents through the ocean basins, the exchange of momentum, heat, freshwater, and gasses between the ocean and the atmosphere, and the interactions between oceans and rivers, estuaries, sea ice, terrestrial ice, and marginal seas.
