Book picks similar to
Data Structures (SIE) by Seymour Lipschutz
cs
data-structure
gg
maths
Get Your Hands Dirty on Clean Architecture: A hands-on guide to creating clean web applications with code examples in Java
Tom Hombergs - 2019
Machine Learning for Hackers
Drew Conway - 2012
Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you'll learn how to analyze sample datasets and write simple machine learning algorithms. "Machine Learning for Hackers" is ideal for programmers from any background, including business, government, and academic research.Develop a naive Bayesian classifier to determine if an email is spam, based only on its textUse linear regression to predict the number of page views for the top 1,000 websitesLearn optimization techniques by attempting to break a simple letter cipherCompare and contrast U.S. Senators statistically, based on their voting recordsBuild a "whom to follow" recommendation system from Twitter data
Introduction to Machine Learning with Python: A Guide for Data Scientists
Andreas C. Müller - 2015
If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn:Fundamental concepts and applications of machine learningAdvantages and shortcomings of widely used machine learning algorithmsHow to represent data processed by machine learning, including which data aspects to focus onAdvanced methods for model evaluation and parameter tuningThe concept of pipelines for chaining models and encapsulating your workflowMethods for working with text data, including text-specific processing techniquesSuggestions for improving your machine learning and data science skills
The Non-Designer's Design Book
Robin P. Williams - 2003
Not to worry: This book is the one place you can turn to find quick, non-intimidating, excellent design help. In The Non-Designer's Design Book, 2nd Edition, best-selling author Robin Williams turns her attention to the basic principles of good design and typography. All you have to do is follow her clearly explained concepts, and you'll begin producing more sophisticated, professional, and interesting pages immediately. Humor-infused, jargon-free prose interspersed with design exercises, quizzes, illustrations, and dozens of examples make learning a snap—which is just what audiences have come to expect from this best-selling author.
Deep Learning with Python
François Chollet - 2017
It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.
The Design of Everyday Things
Donald A. Norman - 1988
It could forever change how you experience and interact with your physical surroundings, open your eyes to the perversity of bad design and the desirability of good design, and raise your expectations about how things should be designed.B & W photographs and illustrations throughout.
OCA Java SE 7 Programmer I Certification Guide: Prepare for the 1ZO-803 exam
Mala Gupta - 2012
You'll explore a wide range of important Java topics as you systematically learn how to pass the certification exam. Each chapter starts with a list of the exam objectives covered in that chapter. You'll find sample questions and exercises designed to reinforce key concepts and to prepare you for what you'll see in the real exam, along with numerous tips, notes, and visual aids throughout the book.About This BookTo earn the OCA Java SE 7 Programmer Certification, you need to know your Java inside and out, and to pass the exam it's good to understand the test itself. This book cracks open the questions, exercises, and expectations you'll face on the OCA exam so you'll be ready and confident on test day.OCA Java SE 7 Programmer I Certification Guide is a comprehensive guide to the 1Z0-803 exam. You'll explore important Java topics as you systematically learn what is required. Each chapter starts with a list of exam objectives, followed by sample questions and exercises designed to reinforce key concepts. It provides multiple ways to digest important techniques and concepts, including analogies, diagrams, flowcharts, and lots of well-commented code.Written for developers with a working knowledge of Java who want to earn the OCA Java SE 7 Programmer I Certification.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.What's InsideCovers all exam topicsHands-on coding exercisesHow to avoid built-in traps and pitfallsAbout the AuthorMala Gupta has been training programmers to pass Java certification exams since 2006. She holds OCA Java SE7 Programmer I, SCWCD, and SCJP certifications.Table of ContentsIntroductionJava basicsWorking with Java data typesMethods and encapsulationString, StringBuilder, Arrays, and ArrayListFlow controlWorking with inheritanceException handlingFull mock exam
Algorithms
Sanjoy Dasgupta - 2006
Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal. Features include: The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated.Carefully chosen advanced topics that can be skipped in a standard one-semester course, but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence.An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms. An optional chapter on the quantum algorithm for factoring provides a unique peephole into this exciting topic. In addition to the text, DasGupta also offers a Solutions Manual, which is available on the Online Learning Center.Algorithms is an outstanding undergraduate text, equally informed by the historical roots and contemporary applications of its subject. Like a captivating novel, it is a joy to read. Tim Roughgarden Stanford University
Design Data Handbook for Mechanical Engineers in Si and Metric Units
K. Mahadevan - 2018
Working out the design of a machine as a whole, or its components, usually involvesthe use of several formulae, graphs, standard tables and other relevant data. Availability of all such information in one handbook not only eliminates the unnecessary task ot remembering the required formulae and equations, but also helps design engineers to solve the problems in machine design quickly and efficiently.This handbook has been prepared keeping these basics in mind. References have been made to several standard textbooks on machine design while compiling the data of this book. In the preparation of the fourth edition, most of the chapters and topics have been upgraded and improved by adding additional information on current design.
Cassandra: The Definitive Guide
Eben Hewitt - 2010
Cassandra: The Definitive Guide provides the technical details and practical examples you need to assess this database management system and put it to work in a production environment.Author Eben Hewitt demonstrates the advantages of Cassandra's nonrelational design, and pays special attention to data modeling. If you're a developer, DBA, application architect, or manager looking to solve a database scaling issue or future-proof your application, this guide shows you how to harness Cassandra's speed and flexibility.Understand the tenets of Cassandra's column-oriented structureLearn how to write, update, and read Cassandra dataDiscover how to add or remove nodes from the cluster as your application requiresExamine a working application that translates from a relational model to Cassandra's data modelUse examples for writing clients in Java, Python, and C#Use the JMX interface to monitor a cluster's usage, memory patterns, and moreTune memory settings, data storage, and caching for better performance
Data Structures and Algorithms Made Easy in Java: 700 Data Structure and Algorithmic Puzzles
Narasimha Karumanchi - 2011
Success key books for: Programming puzzles for interviews Campus Preparation Degree/Masters Course Preparation Instructor's GATE Preparation Big job hunters: Microsoft, Google, Amazon, Yahoo, Flip Kart, Adobe, IBM Labs, Citrix, Mentor Graphics, NetApp, Oracle, Webaroo, De-Shaw, Success Factors, Face book, McAfee and many more Reference Manual for working people
Life After Google: The Fall of Big Data and the Rise of the Blockchain Economy
George Gilder - 2018
Gilder says or writes is ever delivered at anything less than the fullest philosophical decibel... Mr. Gilder sounds less like a tech guru than a poet, and his words tumble out in a romantic cascade." “Google’s algorithms assume the world’s future is nothing more than the next moment in a random process. George Gilder shows how deep this assumption goes, what motivates people to make it, and why it’s wrong: the future depends on human action.” — Peter Thiel, founder of PayPal and Palantir Technologies and author of Zero to One: Notes on Startups, or How to Build the Future The Age of Google, built on big data and machine intelligence, has been an awesome era. But it’s coming to an end. In Life after Google, George Gilder—the peerless visionary of technology and culture—explains why Silicon Valley is suffering a nervous breakdown and what to expect as the post-Google age dawns. Google’s astonishing ability to “search and sort” attracts the entire world to its search engine and countless other goodies—videos, maps, email, calendars….And everything it offers is free, or so it seems. Instead of paying directly, users submit to advertising. The system of “aggregate and advertise” works—for a while—if you control an empire of data centers, but a market without prices strangles entrepreneurship and turns the Internet into a wasteland of ads. The crisis is not just economic. Even as advances in artificial intelligence induce delusions of omnipotence and transcendence, Silicon Valley has pretty much given up on security. The Internet firewalls supposedly protecting all those passwords and personal information have proved hopelessly permeable. The crisis cannot be solved within the current computer and network architecture. The future lies with the “cryptocosm”—the new architecture of the blockchain and its derivatives. Enabling cryptocurrencies such as bitcoin and ether, NEO and Hashgraph, it will provide the Internet a secure global payments system, ending the aggregate-and-advertise Age of Google. Silicon Valley, long dominated by a few giants, faces a “great unbundling,” which will disperse computer power and commerce and transform the economy and the Internet. Life after Google is almost here. For fans of "Wealth and Poverty," "Knowledge and Power," and "The Scandal of Money."
Head First JavaScript Programming
Eric Freeman - 2014
Want to understand that code you've been copying and pasting into your web pages? And do it in a way that won't put you to sleep? Then Head First JavaScript Programming is for you. Learning a programming language is no easy task, but Head First JavaScript Programming uses puzzles, visuals, mysteries, interviews, and fun examples to make learning JavaScript fast, fun, and effective. But don't be fooled; you might be having a good time while you're learning JavaScript, but you're still learning all the serious stuff. Like how functions and objects work, what a callback is, how to interact with the web page using the Document Object Model, how to use arrays, and even what a closure is. JavaScript is one of the most popular languages in the world, and it's only getting more popular as the Web continues to grow. Learn JavaScript the Head First way, and get in on all the action.
A Smarter Way to Learn Python: Learn it faster. Remember it longer.
Mark Myers - 2017
I was smart enough to earn an honors degree in philosophy from Harvard, but an aptitude test told me to avoid computer programming. I'm sure it was right. But then I designed a learning system for myself that quadrupled my aptitude for learning computer languages. It worked so well for me that I've used it to teach coding to grandmothers, cab drivers, musicians, and 50,000 other newbies.
"Mark Myers' method of getting what can be...difficult information into a format that makes it exponentially easier to consume, truly understand, and synthesize into real-world application is beyond anything I've encountered before." —Amazon reviewer Jason A. Ruby reviewing my first book, A Smarter Way to Learn JavaScript
Quadruple your learning ability.
Washington University research shows that a key teaching method I use—interactive recall practice—improves learning performance 400 percent.
"I don't feel lost and I don't feel that I am forgetting things as I go along." —Amazon reviewer Leonie M. reviewing my second book, A Smarter Way to Learn HTML and CSS
Understanding is easy. Remembering is hard.
Computer languages are not inherently hard to understand, even for non-techies. Remembering is the problem. If you remember all of Chapter 1 through Chapter 10, you'll understand Chapter 11. But you don't remember. Though you read and read, most of it doesn't stick. You don't have a solid foundation to build on. Halfway through the book, it all collapses. That's when most people give up."I've signed up to a few sites like Udemy, Codecademy, FreeCodeCamp, Lynda, YouTube videos, even searched on Coursera but nothing seemed to work for me. This book takes only 10 minutes each chapter and after that, you can exercise what you've just learned right away!" —Amazon reviewer Constanza Morales reviewing my first book, A Smarter Way to Learn JavaScript
Interactive exercises make it stick.
Research shows that you will remember everything if you're repeatedly asked to recall it. That's the beauty of flash cards. But technology offers an even better way to make information stick. With my book you get almost a thousand interactive exercises—they're free online—that embed the whole book in your memory. Algorithms check your work to make sure you know what you think you know. When you stumble, you do the exercise again. You keep trying until you know the chapter cold.
"Not only do the exercises make learning fun, they reinforce the material right away so it sinks in deeper." —Amazon reviewer Timothy B. Miller reviewing my second book, A Smarter Way to Learn HTML and CSS
You won't get bored or sleepy.
The exercises keep you engaged, give you extra practice where you're shaky, and prepare you for each next step. Every lesson is built on top of a solid foundation that you and I have carefully constructed. Each individual step is small. But all the little steps add up to real knowledge—knowledge that you retain.
I finally feel like I KNOW it and won't need to look up the syntax each time..." —Amazon reviewer J. Caritas reviewing my third book, A Smarter Way to Learn jQuery
Really, it ain't that hard.