"More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems."

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    In the second edition of Network Security, this most distinguished of author teams draws on hard-won experience to explain every facet of information security, from the basics to advanced cryptography and authentication; secure Web and email services; and emerging security standards. Highlights of the book's extensive new coverage include Advanced Encryption Standard (AES), IPsec, SSL, PKI Standards, and Web security.

    Packed with practical recipes written and tested with Python 3.3, this unique cookbook is for experienced Python programmers who want to focus on modern tools and idioms.Inside, you’ll find complete recipes for more than a dozen topics, covering the core Python language as well as tasks common to a wide variety of application domains. Each recipe contains code samples you can use in your projects right away, along with a discussion about how and why the solution works.Topics include:Data Structures and AlgorithmsStrings and TextNumbers, Dates, and TimesIterators and GeneratorsFiles and I/OData Encoding and ProcessingFunctionsClasses and ObjectsMetaprogrammingModules and PackagesNetwork and Web ProgrammingConcurrencyUtility Scripting and System AdministrationTesting, Debugging, and ExceptionsC Extensions

    While it's safe to say that relational databases aren't going anywhere, we can also say that the ecosystem around data is never going to be the same.Of all the new tools and solutions, for me, Redis has been the most exciting. Why? First because it's unbelievably easy to learn. Hours is the right unit to use when talking about length of time it takes to get comfortable with Redis. Secondly, it solves a specific set of problems while at the same time being quite generic. What exactly does that mean? Redis doesn't try to be all things to all data. As you get to know Redis, it'll become increasingly evident what does and what does not belong in it. And when it does, as a developer, it's a great experience.While you can build a complete system using Redis only, I think most people will find that it supplements their more generic data solution - whether that be a traditional relational database, a document-oriented system, or something else. It's the kind of solution you use to implement specific features. In that way, it's similar to an indexing engine. You wouldn't build your entire application on Lucene. But when you need good search, it's a much better experience - for both you and your users. Of course, the similarities between Redis and indexing engines end there.The goal of this book is to build the foundation you'll need to master Redis. We'll focus on learning Redis' five data structures and look at various data modeling approaches. We'll also touch on some key administrative details and debugging techniques.LicenseThe Little Redis Book is licensed under the Attribution-NonCommercial 3.0 Unported license. You should not have paid for this book.You are free to copy, distribute, modify or display the book. However, I ask that you always attribute the book to me, Karl Seguin, and do not use it for commercial purposes.You can see the full text of the license at:http://creativecommons.org/licenses/b...About The AuthorKarl Seguin is a developer with experience across various fields and technologies. He's an active contributor to Open-Source Software projects, a technical writer and an occasional speaker. He's written various articles, as well as a few tools, about Redis. Redis powers the ranking and statistics of his free service for casual game developers: mogade.com.Karl wrote The Little MongoDB Book, the free and popular book about MongoDB.His blog can be found at http://openmymind.net and he tweets via @karlseguinWith Thanks ToA special thanks to Perry Neal for lending me his eyes, mind and passion. You provided me with invaluable help. Thank you.Latest VersionThe latest source of this book is available at: http://github.com/karlseguin/the-litt...

    A complete overview of shell programming This classic edition deals specifically with the techniques of shell programming.-- Presents information in step-by-step fashion-- Covers all the features of the standard shell, with additional instructions for the Korn Shell-- Teaches how to use the shell to tailor the UNIX environment

     This new edition has an earlier evolution of object concepts, developed in a way that capitalizes on the power of objects without overwhelming beginning programmers. It includes all new Java 5 topics, including Scanner class, enumerated types, autoboxing, variable length parameter lists, the enhanced for loop, and generic types. This is in depth coverage on GUI applications. This book is appropriate for beginning programmers who want to learn to program with Java as well as experienced programmers who want to add Java to their skill-set.

    It includes a complete chapter on C++ and an overall organization designed to appeal to the many programmers who view C as a stepping stone to C++ and the object-oriented paradigm. This edition also features an increased emphasis on modules and ADTs, which are essential concepts for creating reusable code and which show how to use header files to tie together a multi-file program. computer science students.

    It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It's ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it's specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples

    This third edition is the best resource for quick, no-nonsense insights into understanding and using UML 2.0 and prior versions of the UML. Some readers will want to quickly get up to speed with the UML 2.0 and learn the essentials of the UML. Others will use this book as a handy, quick reference to the most common parts of the UML. The author delivers on both of these promises in a short, concise, and focused presentation. This book describes all the major UML diagram types, what they're used for, and the basic notation involved in creating and deciphering them. These diagrams include class, sequence, object, package, deployment, use case, state machine, activity, communication, composite structure, component, interaction overview, and timing diagrams. The examples are clear and the explanations cut to the fundamental design logic. Includes a quick reference to the most useful parts of the UML notation and a useful summary of diagram types that were added to the UML 2.0. If you are like most developers, you don't have time to keep up with all the new innovations in software engineering. This new edition of Fowler's classic work gets you acquainted with some of the best thinking about efficient object-oriented software design using the UML--in a convenient format that will be essential to anyone who designs software professionally.

    You d be up to your neck in normal forms before you even had a chance to wade. When Michael J. Hernandez needed a database design book to teach mere mortals like himself, there were none. So he began a personal quest to learn enough to write one. And he did.Now in its Second Edition, Database Design for Mere Mortals is a miracle for today s generation of database users who don t have the background -- or the time -- to learn database design the hard way. It s also a secret pleasure for working pros who are occasionally still trying to figure out what they were taught.Drawing on 13 years of database teaching experience, Hernandez has organized database design into several key principles that are surprisingly easy to understand and remember. He illuminates those principles using examples that are generic enough to help you with virtually any application.Hernandez s goals are simple. You ll learn how to create a sound database structure as easily as possible. You ll learn how to optimize your structure for efficiency and data integrity. You ll learn how to avoid problems like missing, incorrect, mismatched, or inaccurate data. You ll learn how to relate tables together to make it possible to get whatever answers you need in the future -- even if you haven t thought of the questions yet.If -- as is often the case -- you already have a database, Hernandez explains how to analyze it -- and leverage it. You ll learn how to identify new information requirements, determine new business rules that need to be applied, and apply them.Hernandez starts with an introduction to databases, relational databases, and the idea and objectives of database design. Next, you ll walk through the key elements of the database design process: establishing table structures and relationships, assigning primary keys, setting field specifications, and setting up views. Hernandez s extensive coverage of data integrity includes a full chapter on establishing business rules and using validation tables.Hernandez surveys bad design techniques in a chapter on what not to do -- and finally, helps you identify those rare instances when it makes sense to bend or even break the conventional rules of database design.There s plenty that s new in this edition. Hernandez has gone over his text and illustrations with a fine-tooth comb to improve their already impressive clarity. You ll find updates to reflect new advances in technology, including web database applications. There are expanded and improved discussions of nulls and many-to-many relationships; multivalued fields; primary keys; and SQL data type fields. There s a new Quick Reference database design flowchart. A new glossary. New review questions at the end of every chapter.Finally, it s worth mentioning what this book isn t. It isn t a guide to any specific database platform -- so you can use it whether you re running Access, SQL Server, or Oracle, MySQL or PostgreSQL. And it isn t an SQL guide. (If that s what you need, Michael J. Hernandez has also coauthored the superb SQL Queries for Mere Mortals). But if database design is what you need to learn, this book s worth its weight in gold. Bill CamardaBill Camarda is a consultant, writer, and web/multimedia content developer. His 15 books include Special Edition Using Word 2000 and Upgrading & Fixing Networks for Dummies, Second Edition.

    Daniel Liang teaches concepts of problem-solving and object-oriented programming using a fundamentals-first approach. Beginning programmers learn critical problem-solving techniques then move on to grasp the key concepts of object-oriented and GUI programming using Java 5. Students start with the essential problem-solving and programming concepts (control statements, methods, and arrays), are then introduced to object-oriented programming, graphical user interface (GUI), and applets, and finally to exception handling, I/O, data structures, and other advanced subjects. Liang uses small, simple, and stimulating examples to demonstrate concepts and techniques while longer examples are presented in case studies with overall discussions and thorough line-by-line explanations. Students can now write short, interesting, graphical game programs starting from Chapter 2! reinforcing key concepts with objectives lists, introduction and chapter overviews, easy to follow examples, chapter summaries, review questions, programming exercises, interactive self-test. Students receive solutions to even-numbered programming exercises, source code for the examples in the book, online self assessment (w/over 1000 multiple-choice questions) and ONLINE homework through GRADIANCE, the industries most advanced online homework application. Instructors are offered the most extensive library of support materials available including interactive and animated slides, TestGen (w/over 2000 multiple-choice questions), solutions to all programming exercises, sample exams and supplemental exercises. Available in two versions, the Fundamentals First edition (chapters 1-19) and the Comprehensive version (chapters 1-36).

    With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems.Learn how different organizations are using graph databases to outperform their competitors. With this book’s data modeling, query, and code examples, you’ll quickly be able to implement your own solution.Model data with the Cypher query language and property graph modelLearn best practices and common pitfalls when modeling with graphsPlan and implement a graph database solution in test-driven fashionExplore real-world examples to learn how and why organizations use a graph databaseUnderstand common patterns and components of graph database architectureUse analytical techniques and algorithms to mine graph database information

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.