Best Computer Engineering

The added chapters contain (1) a crisp condensation of all the propositions asserted in the original book, including Brooks' central argument in The Mythical Man-Month: that large programming projects suffer management problems different from small ones due to the division of labor; that the conceptual integrity of the product is therefore critical; and that it is difficult but possible to achieve this unity; (2) Brooks' view of these propositions a generation later; (3) a reprint of his classic 1986 paper "No Silver Bullet"; and (4) today's thoughts on the 1986 assertion, "There will be no silver bullet within ten years." My co-authors of that study, and our executive secretary, Robert L. Patrick, were invaluable in bringing me back into touch with real-world large software projects. In preparing my retrospective and update of The Mythical Man-Month, I was struck by how few of the propositions asserted in it have been critiqued, proven, or disproven by ongoing software engineering research and experience. In hopes that these bald statements will invite arguments and facts to prove, disprove, update, or refine those propositions, I have included this outline as Chapter 18. For a wonderful willingness to share views, to comment thoughtfully on drafts, and to re-educate me, I am indebted to Barry Boehm, Ken Brooks, Dick Case, James Coggins, Tom DeMarco, Jim McCarthy, David Parnas, Earl Wheeler, and Edward Yourdon. I thank Gordon Bell, Bruce Buchanan, Rick Hayes-Roth, my colleagues on the Defense Science Board Task Force on Military Software, and, most especially, David Parnas for their insights and stimulating ideas for, and Rebekah Bierly for technical production of, the paper printed here as Chapter 16. Analyzing the software problem into the categories of essence and accident was inspired by Nancy Greenwood Brooks, who used such analysis in a paper on Suzuki violin pedagogy. Two persons' contributions should be especially cited: Norman Stanton, then Executive Editor, and Herbert Boes, then Art Director. Boes developed the elegant style, which one reviewer especially cited: "wide margins, and imaginative use of typeface and layout."

The pros and cons of braced initialization, noexcept specifications, perfect forwarding, and smart pointer make functions The relationships among std::move , std::forward , rvalue references, and universal references Techniques for writing clear, correct, effective lambda expressions How std::atomic differs from volatile , how each should be used, and how they relate to C++'s concurrency API How best practices in "old" C++ programming (i.e., C++98) require revision for software development in modern C++. Effective Modern C++ is the most important how-to book for advice on key guidelines, styles, and idioms to use modern C++ effectively and well. For more than 20 years, Scott Meyers’ Effective C++ books (Effective C++, More Effective C++, and Effective STL) have set the bar for C++ programming guidance.

Mapping Multi-Tier Architectures to AWS Services, such as web/app servers, firewalls, caches and load balancers Understanding managed RDBMS through AWS RDS (MySQL, Oracle, SQL Server, Postgres, Aurora) Understanding Loose Coupling and Stateless Systems Comparing Different Consistency Models in AWS Services Understanding how AWS CloudFront can make your application more cost efficient, faster and secure Implementing Route tables, Access Control Lists, Firewalls, NAT, and DNS Applying AWS Security Features along with traditional Information and Application Security Using Compute, Networking, Storage, and Database AWS services Architecting Large Scale Distributed Systems Understanding of Elasticity and Scalability Concepts Understanding of Network Technologies Relating to AWS Deploying and Managing Services with tools such as CloudFormation, OpsWorks and Elastic Beanstalk. Your complete guide to preparing for the AWS Certified Solutions Architect — Associate Exam. The AWS Certified Solutions Architect Official Study Guide is your one-stop resource for coverage of the Associate Level Exam. Mapping Multi-Tier Architectures to AWS Services, such as web/app servers, firewalls, caches, and load balancers Understanding managed RDBMS through AWS RDS (MySQL ® , Oracle ® , SQL Server ® , Postgres, Aurora) Understanding Loose Coupling and Stateless Systems Comparing Different Consistency Models in AWS Services Understanding how AWS CloudFront can make your application more cost efficient, faster, and secure Implementing Route tables, Access Control Lists, Firewalls, NAT, and DNS Applying AWS Security Features along with traditional Information and Application Security Using Compute, Networking, Storage, and Database AWS services Architecting Large Scale Distributed Systems Understanding of Elasticity and Scalability Concepts Understanding of Network Technologies Relating to AWS Deploying and Managing Services with tools such as CloudFormation, OpsWorks, and Elastic Beanstalk. The AWS Certified Solutions Architect – Associate Exam is intended for individuals with experience designing distributed applications and systems on the AWS Cloud.

Creative professionals seeking the fastest, easiest, most comprehensive way to learn Adobe Photoshop choose Adobe Photoshop CC Classroom in a Book (2017 release) from Adobe Press. Conrad Chavez has provided education, training, and support for digital-media applications for over 20 years, originally contributing countless pages to the user guides for print, Web, and digital video products at Aldus Corporation and Adobe Systems Inc. Now a freelance writer and editor, Conrad creates books and videos that teach Adobe Photoshop and Adobe Creative Cloud workflows. His work includes the last three editions of Real World Adobe Photoshop for Photographers and the video Color Management for Photographers and Designers .

Using the Smarter Way to Learn method, you actually learn HTML/CSS, you don’t just read about it. Read the reviews that call The Smarter Way of learning fun, involving, frustration-free, and confidence-building. Then, if you want to go beyond reading about HTML & CSS and actually learn the skills, do it the smarter way.

Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart , author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. "When Mr. Foreman interviewed for a job at my company, he arrived dressed in a 'Kentucky Colonel' kind of suit and spoke about nonsensical things like barbecue, lasers, and orange juice pulp. After reading this book, you too will learn how to use math and basic spreadsheet formulas to improve your business or, at the very least, how to trick senior executives into hiring you as their data scientist." This book shows you the significant data science techniques, how they work, how to use them, and how they benefit your business, large or small. Artificial intelligence using the general linear model, ensemble methods, and naive Bayes Clustering via k-means, spherical k-means, and graph modularity Mathematical optimization, including non-linear programming and genetic algorithms Working with time series data and forecasting with exponential smoothing Using Monte Carlo simulation to quantify and address risk Detecting outliers in single or multiple dimensions Exploring the data-science-focused R language. As an analytics consultant, John has created data science solutions for The Coca-Cola Company, Royal Caribbean International, Intercontinental Hotels Group, Dell, the Department of Defense, the IRS, and the FBI.

User experience (UX) strategy requires a careful blend of business strategy and UX design, but until now, there hasn’t been an easy-to-apply framework for executing it.

This is the eBook version of the printed book. Essential Information about Algorithms and Data Structures. The latest version of Sedgewick’s best-selling series, reflecting an indispensable body of knowledge developed over the past several decades. Full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing, including fifty algorithms every programmer should know. New Java implementations written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use. Algorithms are studied in the context of important scientific, engineering, and commercial applications. Clients and algorithms are expressed in real code, not the pseudo-code found in many other books. Engages reader interest with clear, concise text, detailed examples with visuals, carefully crafted code, historical and scientific context, and exercises at all levels. Develops precise statements about performance, supported by appropriate mathematical models and empirical studies validating those models. Robert Sedgewick has been a Professor of Computer Science at Princeton University since 1985, where he was the founding Chairman of the Department of Computer Science.

In CODE, they show us the ingenious ways we manipulate language and invent new means of communicating with each other. Charles Petzold's latest book, Code: The Hidden Language of Computer Hardware and Software , crosses over into general-interest nonfiction from his usual programming genre. From Louis Braille's development of his eponymous raised-dot code to Intel Corporation's release of its early microprocessors, Petzold presents stories of people trying to communicate with (and by means of) mechanical and electrical devices. The real value of Code is in its explanation of technologies that have been obscured for years behind fancy user interfaces and programming environments, which, in the name of rapid application development, insulate the programmer from the machine.

Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. "This timely book says out loud what has finally become apparent: in the modern world, Data is Business, and you can no longer think business without thinking data. Read this book and you will understand the Science behind thinking data." "A great book for business managers who lead or interact with data scientists, who wish to better understand the principles and algorithms available without the technical details of single-disciplinary books." What you need to know about data mining and data-analytic thinking.

Explore the machine learning landscape, particularly neural nets Use scikit-learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets Apply practical code examples without acquiring excessive machine learning theory or algorithm details. He was also a founder and CTO of Wifirst from 2002 to 2012, a leading Wireless ISP in France, and a founder and CTO of Polyconseil in 2001, the firm that now manages the electric car sharing service Autolib'.Before this he worked as an engineer in a variety of domains: finance (JP Morgan and Société Générale), defense (Canada's DOD), and healthcare (blood transfusion).