Want to impress your coworkers and write the fastest, most efficient, stable code you ever have? Don't reinvent the wheel. Reuse decades of research into battle-tested, highly optimized, and proven techniques available on any Unix system.This book will teach you what you need to know so that you can write your own servers, debug your entire stack when things go awry, and understand how things are working under the hood.http://www.jstorimer.com/products/wor...

    However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes - Learning the Bayesian "state of mind" and its practical implications - Understanding how computers perform Bayesian inference - Using the PyMC Python library to program Bayesian analyses - Building and debugging models with PyMC - Testing your model's "goodness of fit" - Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works - Leveraging the power of the "Law of Large Numbers" - Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning - Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes - Selecting appropriate priors and understanding how their influence changes with dataset size - Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough - Using Bayesian inference to improve A/B testing - Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

    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.

    The Unwritten Laws of Business is such a book. Originally published over 60 years ago as The Unwritten Laws of Engineering, it has sold over 100,000 copies, despite the fact that it has never been available before to general readers. Fully revised for business readers today, here are but a few of the gems you’ll find in this little-known business classic: If you take care of your present job well, the future will take care of itself.The individual who says nothing is usually credited with having nothing to say.Whenever you are performing someone else’s function, you are probably neglecting your own.Martyrdom only rarely makes heroes, and in the business world, such heroes and martyrs often find themselves unemployed.Refreshingly free of the latest business fads and jargon, this is a book that is wise and insightful, capturing and distilling the timeless truths and principles that underlie management and business the world over.The little book with the big history.In the summer of 2005, Business 2.0 published a cover story on Raytheon CEO William Swanson’s self-published pamphlet, Swanson’s Unwritten Rules of Management. Lauded by such chief executives as Jack Welch and Warren Buffett, the booklet becamea quiet phenomenon. As it turned out, much of Swanson’s book drew from a classic of business literature that has been in print for more than sixty years. Now, in a new edition revised and updated for business readers today, we are reissuing the 1944 classic that inspired a number of Swanson’s “rules”: The Unwritten Laws of Business. Filled with sage advice and written in a spare, engaging style, The Unwritten Laws of Business offers insights on working with others, reporting to a boss, organizing a project, running a meeting, advancing your career, and more. Here’s just a sprinkling of the old-fashioned, yet surprisingly relevant, wisdom you’ll find in these pages:If you have no intention of listening to, considering, and perhaps using, someone’s opinion, don’t ask for it.Count any meeting a failure that does not end up with a definite understanding as to what’s going to be done, who’s going to do it, and when.The common belief that everyone can do anything if they just try hard enough is a formula for inefficiency at best and for complete failure at worst.It is natural enough to “look out for Number One first,” but when you do, your associates will be noticeably disinclined to look out for you.Whether you’re a corporate neophyte or seasoned manager, this charming book reveals everything you need to know about the “unwritten” laws of business.

    A no-nonsense tutorial and reliable reference, this book features thoroughly tested real-world examples. The most important language and library features are demonstrated with deliberately simple sample programs, but they aren't fake and they don't cut corners. More importantly, all of the programs have been updated for J2SE 5.0 and should make good starting points for your own code. You won't find any toy examples here. This is a book for programmers who want to write real code to solve real problems. Cay S. Horstmann is a professor of computer science at San Jose State University. Previously he was vice president and chief technology officer of Preview Systems Inc. and a consultant on C++, Java, and Internet programming for major corporations, universities, and organizations. Gary Cornell has written or cowritten more than twenty popular computer books. He has a Ph.D. from Brown University and has been a visiting scientist at IBM Watson Laboratories, as well as a professor at the University of Connecticut.

    The Web is awash in Ruby code that is now virtually impossible to change or extend. This text helps you solve that problem by using powerful real-world object-oriented design techniques, which it thoroughly explains using simple and practical Ruby examples. Sandi Metz has distilled a lifetime of conversations and presentations about object-oriented design into a set of Ruby-focused practices for crafting manageable, extensible, and pleasing code. She shows you how to build new applications that can survive success and repair existing applications that have become impossible to change. Each technique is illustrated with extended examples, all downloadable from the companion Web site, poodr.info. The first title to focus squarely on object-oriented Ruby application design, Practical Object-Oriented Design in Ruby will guide you to superior outcomes, whatever your previous Ruby experience. Novice Ruby programmers will find specific rules to live by; intermediate Ruby programmers will find valuable principles they can flexibly interpret and apply; and advanced Ruby programmers will find a common language they can use to lead development and guide their colleagues. This guide will help you Understand how object-oriented programming can help you craft Ruby code that is easier to maintain and upgrade Decide what belongs in a single Ruby class Avoid entangling objects that should be kept separate Define flexible interfaces among objects Reduce programming overhead costs with duck typing Successfully apply inheritance Build objects via composition Design cost-effective tests Solve common problems associated with poorly designed Ruby code

    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.

    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.

    Until now. This practical guide provides the first comprehensive overview of software architecture's many aspects. You'll examine architectural characteristics, architectural patterns, component determination, diagramming and presenting architecture, evolutionary architecture, and many other topics.Authors Neal Ford and Mark Richards help you learn through examples in a variety of popular programming languages, such as Java, C#, JavaScript, and others. You'll focus on architecture principles with examples that apply across all technology stacks.

    The Windows Command Line Beginner's Guide gives users new to the Windows command line an overview of the Command Prompt, from simple tasks to network configuration.In the Guide, you'll learn how to:-Manage the Command Prompt.-Copy & paste from the Windows Command Prompt.-Create batch files.-Remotely manage Windows machines from the command line.-Manage disks, partitions, and volumes.-Set an IP address and configure other network settings.-Set and manage NTFS and file sharing permissions.-Customize and modify the Command Prompt.-Create and manage file shares.-Copy, move, and delete files and directories from the command line.-Manage PDF files and office documents from the command line.-And many other topics.

    Why is this open-source tool so popular? Because it automates a tedious task: persisting your Java objects to a relational database. The inevitable mismatch between your object-oriented code and the relational database requires you to write code that maps one to the other. This code is often complex, tedious and costly to develop. Hibernate does the mapping for you.Not only that, Hibernate makes it easy. Positioned as a layer between your application and your database, Hibernate takes care of loading and saving of objects. Hibernate applications are cheaper, more portable, and more resilient to change. And they perform better than anything you are likely to develop yourself."Hibernate in Action" carefully explains the concepts you need, then gets you going. It builds on a single example to show you how to use Hibernate in practice, how to deal with concurrency and transactions, how to efficiently retrieve objects and use caching.The authors created Hibernate and they field questions from the Hibernate community every day-they know how to make Hibernate sing. Knowledge and insight seep out of every pore of this book."What's Inside"- ORM concepts- Getting started- Many real-world tasks- The Hibernate application development process

    This concise book guides you into and through JavaScript, written by a veteran programmer who once found himself in the same position. Speaking JavaScript helps you approach the language with four standalone sections. First, a quick-start guide teaches you just enough of the language to help you be productive right away. More experienced JavaScript programmers will find a complete and easy-to-read reference that covers each language feature in depth. Complete contents include: JavaScript quick start: Familiar with object-oriented programming? This part helps you learn JavaScript quickly and properly. JavaScript in depth: Learn details of ECMAScript 5, from syntax, variables, functions, and object-oriented programming to regular expressions and JSON with lots of examples. Pick a topic and jump in. Background: Understand JavaScript’s history and its relationship with other programming languages. Tips, tools, and libraries: Survey existing style guides, best practices, advanced techniques, module systems, package managers, build tools, and learning resources.

    unsigned numbers- Floating point and fixed point arithmeticThis short, easily understood book will quickly get you thinking like a programmer.

    It guides you through the creation and deployment of a simple webapp, showing how Docker can be used at all stages, including development, testing and deployment.Other topics in this book include using Docker to provide a microservices architecture, how to best do service discovery, and how to bundle applications using Docker. You'll also get an overview of the large ecosystem that has sprung up around Docker, including the various PaaS offerings and configuration tools.

    Readers learn how to reduce time constraints and develop programs efficiently by analyzing the feasibility of an algorithm before it is coded. The C++ language is brought up-to-date and simplified, and the Standard Template Library is now fully incorporated throughout the text. This Third Edition also features significantly revised coverage of lists, stacks, queues, and trees and an entire chapter dedicated to amortized analysis and advanced data structures such as the Fibonacci heap. Known for its clear and friendly writing style, Data Structures and Algorithm Analysis in C++ is logically organized to cover advanced data structures topics from binary heaps to sorting to NP-completeness. Figures and examples illustrating successive stages of algorithms contribute to Weiss' careful, rigorous and in-depth analysis of each type of algorithm.