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.

    The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to take a hard pass on Knuth's brilliant but impenetrable theories and the dense multi-page proofs you'll find in most textbooks, this is the book for you. This fully-illustrated and engaging guide makes it easy for you to learn how to use algorithms effectively in your own programs.Grokking Algorithms is a disarming take on a core computer science topic. In it, you'll learn how to apply common algorithms to the practical problems you face in day-to-day life as a programmer. You'll start with problems like sorting and searching. As you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression or artificial intelligence. Whether you're writing business software, video games, mobile apps, or system utilities, you'll learn algorithmic techniques for solving problems that you thought were out of your grasp. For example, you'll be able to:Write a spell checker using graph algorithmsUnderstand how data compression works using Huffman codingIdentify problems that take too long to solve with naive algorithms, and attack them with algorithms that give you an approximate answer insteadEach carefully-presented example includes helpful diagrams and fully-annotated code samples in Python. By the end of this book, you will know some of the most widely applicable algorithms as well as how and when to use them.

    Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

    As a modern application developer you need to understand the emerging field of data management, both RDBMS and NoSQL. Seven Databases in Seven Weeks takes you on a tour of some of the hottest open source databases today. In the tradition of Bruce A. Tate's Seven Languages in Seven Weeks, this book goes beyond your basic tutorial to explore the essential concepts at the core each technology. Redis, Neo4J, CouchDB, MongoDB, HBase, Riak and Postgres. With each database, you'll tackle a real-world data problem that highlights the concepts and features that make it shine. You'll explore the five data models employed by these databases-relational, key/value, columnar, document and graph-and which kinds of problems are best suited to each. You'll learn how MongoDB and CouchDB are strikingly different, and discover the Dynamo heritage at the heart of Riak. Make your applications faster with Redis and more connected with Neo4J. Use MapReduce to solve Big Data problems. Build clusters of servers using scalable services like Amazon's Elastic Compute Cloud (EC2). Discover the CAP theorem and its implications for your distributed data. Understand the tradeoffs between consistency and availability, and when you can use them to your advantage. Use multiple databases in concert to create a platform that's more than the sum of its parts, or find one that meets all your needs at once.Seven Databases in Seven Weeks will take you on a deep dive into each of the databases, their strengths and weaknesses, and how to choose the ones that fit your needs.What You Need: To get the most of of this book you'll have to follow along, and that means you'll need a *nix shell (Mac OSX or Linux preferred, Windows users will need Cygwin), and Java 6 (or greater) and Ruby 1.8.7 (or greater). Each chapter will list the downloads required for that database.

    You'd like to learn how to do more work with SQL inside the database before pushing data across the network to your applications. You'd like to take your SQL skills to the next level.Let's face it, SQL is a deceptively simple language to learn, and many database developers never go far beyond the simple statement: SELECT columns FROM table WHERE conditions. But there is so much more you can do with the language. In the SQL Cookbook, experienced SQL developer Anthony Molinaro shares his favorite SQL techniques and features. You'll learn about:Window functions, arguably the most significant enhancement to SQL in the past decade. If you're not using these, you're missing outPowerful, database-specific features such as SQL Server's PIVOT and UNPIVOT operators, Oracle's MODEL clause, and PostgreSQL's very useful GENERATE_SERIES functionPivoting rows into columns, reverse-pivoting columns into rows, using pivoting to facilitate inter-row calculations, and double-pivoting a result setBucketization, and why you should never use that term in Brooklyn.How to create histograms, summarize data into buckets, perform aggregations over a moving range of values, generate running-totals and subtotals, and other advanced, data warehousing techniquesThe technique of walking a string, which allows you to use SQL to parse through the characters, words, or delimited elements of a stringWritten in O'Reilly's popular Problem/Solution/Discussion style, the SQL Cookbook is sure to please. Anthony's credo is: When it comes down to it, we all go to work, we all have bills to pay, and we all want to go home at a reasonable time and enjoy what's still available of our days. The SQL Cookbook moves quickly from problem to solution, saving you time each step of the way.

    Over the past few years, incremental developments in core engineering practices for software development have created the foundations for rethinking how architecture changes over time, along with ways to protect important architectural characteristics as it evolves. This practical guide ties those parts together with a new way to think about architecture and time.

    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

    Drawing heavily on the author's own real-world experiences, the book stresses design and analysis. Coverage is divided into two parts, the first being a general guide to techniques for the design and analysis of computer algorithms. The second is a reference section, which includes a catalog of the 75 most important algorithmic problems. By browsing this catalog, readers can quickly identify what the problem they have encountered is called, what is known about it, and how they should proceed if they need to solve it. This book is ideal for the working professional who uses algorithms on a daily basis and has need for a handy reference. This work can also readily be used in an upper-division course or as a student reference guide. THE ALGORITHM DESIGN MANUAL comes with a CD-ROM that contains: * a complete hypertext version of the full printed book. * the source code and URLs for all cited implementations. * over 30 hours of audio lectures on the design and analysis of algorithms are provided, all keyed to on-line lecture notes.

    This is a deeply technical book and focuses on the software engineering skills to ace your interview. The book is over 500 pages and includes 150 programming interview questions and answers, as well as other advice.The full list of topics are as follows:The Interview ProcessThis section offers an overview on questions are selected and how you will be evaluated. What happens when you get a question wrong? When should you start preparing, and how? What language should you use? All these questions and more are answered.Behind the ScenesLearn what happens behind the scenes during your interview, how decisions really get made, who you interview with, and what they ask you. Companies covered include Google, Amazon, Yahoo, Microsoft, Apple and Facebook.Special SituationsThis section explains the process for experience candidates, Program Managers, Dev Managers, Testers / SDETs, and more. Learn what your interviewers are looking for and how much code you need to know.Before the InterviewIn order to ace the interview, you first need to get an interview. This section describes what a software engineer's resume should look like and what you should be doing well before your interview.Behavioral PreparationAlthough most of a software engineering interview will be technical, behavioral questions matter too. This section covers how to prepare for behavioral questions and how to give strong, structured responses.Technical Questions (+ 5 Algorithm Approaches)This section covers how to prepare for technical questions (without wasting your time) and teaches actionable ways to solve the trickiest algorithm problems. It also teaches you what exactly "good coding" is when it comes to an interview.150 Programming Questions and AnswersThis section forms the bulk of the book. Each section opens with a discussion of the core knowledge and strategies to tackle this type of question, diving into exactly how you break down and solve it. Topics covered include• Arrays and Strings• Linked Lists• Stacks and Queues• Trees and Graphs• Bit Manipulation• Brain Teasers• Mathematics and Probability• Object-Oriented Design• Recursion and Dynamic Programming• Sorting and Searching• Scalability and Memory Limits• Testing• C and C++• Java• Databases• Threads and LocksFor the widest degree of readability, the solutions are almost entirely written with Java (with the exception of C / C++ questions). A link is provided with the book so that you can download, compile, and play with the solutions yourself.Changes from the Fourth Edition: The fifth edition includes over 200 pages of new content, bringing the book from 300 pages to over 500 pages. Major revisions were done to almost every solution, including a number of alternate solutions added. The introductory chapters were massively expanded, as were the opening of each of the chapters under Technical Questions. In addition, 24 new questions were added.Cracking the Coding Interview, Fifth Edition is the most expansive, detailed guide on how to ace your software development / programming interviews.

    You'll learn how to:Read and write files efficiently Use signals, clocks, and timers Create processes and execute programs Write secure programs Write multithreaded programs using POSIX threads Build and use shared libraries Perform interprocess communication using pipes, message queues, shared memory, and semaphores Write network applications with the sockets API While The Linux Programming Interface covers a wealth of Linux-specific features, including epoll, inotify, and the /proc file system, its emphasis on UNIX standards (POSIX.1-2001/SUSv3 and POSIX.1-2008/SUSv4) makes it equally valuable to programmers working on other UNIX platforms.The Linux Programming Interface is the most comprehensive single-volume work on the Linux and UNIX programming interface, and a book that's destined to become a new classic.Praise for The Linux Programming Interface "If I had to choose a single book to sit next to my machine when writing software for Linux, this would be it." —Martin Landers, Software Engineer, Google "This book, with its detailed descriptions and examples, contains everything you need to understand the details and nuances of the low-level programming APIs in Linux . . . no matter what the level of reader, there will be something to be learnt from this book." —Mel Gorman, Author of Understanding the Linux Virtual Memory Manager "Michael Kerrisk has not only written a great book about Linux programming and how it relates to various standards, but has also taken care that bugs he noticed got fixed and the man pages were (greatly) improved. In all three ways, he has made Linux programming easier. The in-depth treatment of topics in The Linux Programming Interface . . . makes it a must-have reference for both new and experienced Linux programmers." —Andreas Jaeger, Program Manager, openSUSE, Novell "Michael's inexhaustible determination to get his information right, and to express it clearly and concisely, has resulted in a strong reference source for programmers. While this work is targeted at Linux programmers, it will be of value to any programmer working in the UNIX/POSIX ecosystem." —David Butenhof, Author of Programming with POSIX Threads and Contributor to the POSIX and UNIX Standards ". . . a very thorough—yet easy to read—explanation of UNIX system and network programming, with an emphasis on Linux systems. It's certainly a book I'd recommend to anybody wanting to get into UNIX programming (in general) or to experienced UNIX programmers wanting to know 'what's new' in the popular GNU/Linux system." —Fernando Gont, Network Security Researcher, IETF Participant, and RFC Author ". . . encyclopedic in the breadth and depth of its coverage, and textbook-like in its wealth of worked examples and exercises. Each topic is clearly and comprehensively covered, from theory to hands-on working code. Professionals, students, educators, this is the Linux/UNIX reference that you have been waiting for." —Anthony Robins, Associate Professor of Computer Science, The University of Otago "I've been very impressed by the precision, the quality and the level of detail Michael Kerrisk put in his book. He is a great expert of Linux system calls and lets us share his knowledge and understanding of the Linux APIs." —Christophe Blaess, Author of Programmation systeme en C sous Linux ". . . an essential resource for the serious or professional Linux and UNIX systems programmer. Michael Kerrisk covers the use of all the key APIs across both the Linux and UNIX system interfaces with clear descriptions and tutorial examples and stresses the importance and benefits of following standards such as the Single UNIX Specification and POSIX 1003.1." —Andrew Josey, Director, Standards, The Open Group, and Chair of the POSIX 1003.1 Working Group "What could be better than an encyclopedic reference to the Linux system, from the standpoint of the system programmer, written by none other than the maintainer of the man pages himself? The Linux Programming Interface is comprehensive and detailed. I firmly expect it to become an indispensable addition to my programming bookshelf." —Bill Gallmeister, Author of POSIX.4 Programmer's Guide: Programming for the Real World ". . . the most complete and up-to-date book about Linux and UNIX system programming. If you're new to Linux system programming, if you're a UNIX veteran focused on portability while interested in learning the Linux way, or if you're simply looking for an excellent reference about the Linux programming interface, then Michael Kerrisk's book is definitely the companion you want on your bookshelf." —Loic Domaigne, Chief Software Architect (Embedded), Corpuls.com

    The books also provides a companion web site that provides the toold and materials necessary to build the hardware and software.

    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

    As the words "at work" suggest, Peter Seibel focuses on how his interviewees tackle the day–to–day work of programming, while revealing much more, like how they became great programmers, how they recognize programming talent in others, and what kinds of problems they find most interesting. Hundreds of people have suggested names of programmers to interview on the Coders at Work web site: http://www.codersatwork.com. The complete list was 284 names. Having digested everyone’s feedback, we selected 16 folks who’ve been kind enough to agree to be interviewed:- Frances Allen: Pioneer in optimizing compilers, first woman to win the Turing Award (2006) and first female IBM fellow- Joe Armstrong: Inventor of Erlang- Joshua Bloch: Author of the Java collections framework, now at Google- Bernie Cosell: One of the main software guys behind the original ARPANET IMPs and a master debugger- Douglas Crockford: JSON founder, JavaScript architect at Yahoo!- L. Peter Deutsch: Author of Ghostscript, implementer of Smalltalk-80 at Xerox PARC and Lisp 1.5 on PDP-1- Brendan Eich: Inventor of JavaScript, CTO of the Mozilla Corporation - Brad Fitzpatrick: Writer of LiveJournal, OpenID, memcached, and Perlbal - Dan Ingalls: Smalltalk implementor and designer- Simon Peyton Jones: Coinventor of Haskell and lead designer of Glasgow Haskell Compiler- Donald Knuth: Author of The Art of Computer Programming and creator of TeX- Peter Norvig: Director of Research at Google and author of the standard text on AI- Guy Steele: Coinventor of Scheme and part of the Common Lisp Gang of Five, currently working on Fortress- Ken Thompson: Inventor of UNIX- Jamie Zawinski: Author of XEmacs and early Netscape/Mozilla hackerWhat you’ll learn:How the best programmers in the world do their jobWho is this book for?Programmers interested in the point of view of leaders in the field. Programmers looking for approaches that work for some of these outstanding programmers.

    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

    It's a beautifully written tutorial that begins with the basic steps to get your first Ruby program up and running and goes on to explore sophisticated topics like callable objects, reflection, and threading. Whether the topic is simple or tough, the book's easy-to-follow examples and explanations will give you immediate confidence as you build your Ruby programming skills.The Well-Grounded Rubyist is a thoroughly revised and updated edition of the best-selling Ruby for Rails. In this new book, expert author David A. Black moves beyond Rails and presents a broader view of Ruby. It covers Ruby 1.9, and keeps the same sharp focus and clear writing that made Ruby for Rails stand out.Starting with the basics, The Well-Grounded Rubyist explains Ruby objects and their interactions from the ground up. In the middle chapters, the book turns to an examination of Ruby's built-in, core classes, showing the reader how to manipulate strings, numbers, arrays, ranges, hashes, sets, and more. Regular expressions get attention, as do file and other I/O operations.Along the way, the reader is introduced to numerous tools included in the standard Ruby distribution--tools like the task manager Rake and the interactive Ruby console-based interpreter Irb--that facilitate Ruby development and make it an integrated and pleasant experience.The book encompasses advanced topics, like the design of Ruby's class and module system, and the use of Ruby threads, taking even the new Rubyist deep into the language and giving every reader the foundations necessary to use, explore, and enjoy this unusually popular and versatile language.It's no wonder one reader commented: "The technical depth is just right to not distract beginners, yet detailed enough for more advanced readers."Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.