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Cracking the Coding Interview: 189 Programming Questions and Solutions

By Gayle Laakmann McDowell

CareerCup
Released: 2015-07-01
Paperback (687 pages)

Cracking the Coding Interview: 189 Programming Questions and Solutions
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I am not a recruiter. I am a software engineer. And as such, I know what it's like to be asked to whip up brilliant algorithms on the spot and then write flawless code on a whiteboard. I've been through this as a candidate and as an interviewer.

Cracking the Coding Interview, 6th Edition is here to help you through this process, teaching you what you need to know and enabling you to perform at your very best. I've coached and interviewed hundreds of software engineers. The result is this book.

Learn how to uncover the hints and hidden details in a question, discover how to break down a problem into manageable chunks, develop techniques to unstick yourself when stuck, learn (or re-learn) core computer science concepts, and practice on 189 interview questions and solutions.

These interview questions are real; they are not pulled out of computer science textbooks. They reflect what's truly being asked at the top companies, so that you can be as prepared as possible. WHAT'S INSIDE?
  • 189 programming interview questions, ranging from the basics to the trickiest algorithm problems.
  • A walk-through of how to derive each solution, so that you can learn how to get there yourself.
  • Hints on how to solve each of the 189 questions, just like what you would get in a real interview.
  • Five proven strategies to tackle algorithm questions, so that you can solve questions you haven't seen.
  • Extensive coverage of essential topics, such as big O time, data structures, and core algorithms.
  • A behind the scenes look at how top companies like Google and Facebook hire developers.
  • Techniques to prepare for and ace the soft side of the interview: behavioral questions.
  • For interviewers and companies: details on what makes a good interview question and hiring process.

Deep Learning (Adaptive Computation and Machine Learning series)

By Ian Goodfellow & Aaron Courville

The MIT Press
Hardcover (800 pages)

Deep Learning (Adaptive Computation and Machine Learning series)
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  • The MIT Press
Product Description:

"Written by three experts in the field, Deep Learning is the only comprehensive book on the subject." -- Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX

Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. 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.

Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

By Aurélien Géron

O Reilly Media
Paperback (568 pages)

Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
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  • O Reilly Media
Product Description:

Graphics in this book are printed in black and white.

Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, 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 a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.

  • 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

Introduction to Algorithms, 3rd Edition (MIT Press)

By Thomas H. Cormen & Ronald L. Rivest

imusti
Hardcover (1312 pages)

Introduction to Algorithms, 3rd Edition (MIT Press)
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  • MIT Press MA
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Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor.

The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called "Divide-and-Conquer"), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many new exercises and problems have been added for this edition. As of the third edition, this textbook is published exclusively by the MIT Press.

AWS Certified Solutions Architect Official Study Guide: Associate Exam

By Joe Baron, Tim Bixler, Kevin E. Kelly & John Stamper

SYBEX
Paperback (437 pages)

AWS Certified Solutions Architect Official Study Guide: Associate Exam
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  • SYBEX
Product Description:

Validate your AWS skills. 

This is your opportunity to take the next step in your career by expanding and validating your skills on the AWS cloud.  AWS has been the frontrunner in cloud computing products and services, and the AWS Certified Solutions Architect Official Study Guide for the Associate exam will get you fully prepared through expert content, and real-world knowledge, key exam essentials, chapter review questions, access to Sybex’s interactive online learning environment, and much more. This official study guide, written by AWS experts, covers exam concepts, and provides key review on exam topics, including:

  • 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.

Learn from the AWS subject-matter experts, review with proven study tools, and apply real-world scenarios. If you are looking to take the AWS Certified Solutions Architect Associate exam, this guide is what you need for comprehensive content and robust study tools that will help you gain the edge on exam day and throughout your career. 

A Mind at Play: How Claude Shannon Invented the Information Age

By Jimmy Soni

Simon & Schuster
Released: 2017-07-18
Hardcover (384 pages)

A Mind at Play: How Claude Shannon Invented the Information Age
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“A charming account of one of the twentieth century’s most distinguished scientists…Readers will enjoy this portrait of a modern-day Da Vinci.” —Fortune

The life and times of one of the foremost intellects of the twentieth century: Claude Shannon—the architect of the Information Age, whose insights stand behind every computer built, email sent, video streamed, and webpage loaded.

Claude Shannon was a groundbreaking polymath, a brilliant tinkerer, and a digital pioneer. He constructed a fleet of customized unicycles and a flamethrowing trumpet, outfoxed Vegas casinos, and built juggling robots. He also wrote the seminal text of the digital revolution, which has been called “the Magna Carta of the Information Age.” His discoveries would lead contemporaries to compare him to Albert Einstein and Isaac Newton. His work anticipated by decades the world we’d be living in today—and gave mathematicians and engineers the tools to bring that world to pass.

In this elegantly written, exhaustively researched biography, Jimmy Soni and Rob Goodman reveal Claude Shannon’s full story for the first time. It’s the story of a small-town Michigan boy whose career stretched from the era of room-sized computers powered by gears and string to the age of Apple. It’s the story of the origins of our digital world in the tunnels of MIT and the “idea factory” of Bell Labs, in the “scientists’ war” with Nazi Germany, and in the work of Shannon’s collaborators and rivals, thinkers like Alan Turing, John von Neumann, Vannevar Bush, and Norbert Wiener.

And it’s the story of Shannon’s life as an often reclusive, always playful genius. With access to Shannon’s family and friends, A Mind at Play brings this singular innovator and creative genius to life.

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

By Gareth James & Trevor Hastie

Brand: Springer
Hardcover (426 pages)

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
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An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform.

Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

Systems Analysis and Design (Shelly Cashman Series)

By Scott Tilley

Course Technology
Hardcover (572 pages)

Systems Analysis and Design (Shelly Cashman Series)
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Offer your students a practical, streamlined, and updated approach to information systems development with Tilley/Rosenblatt's SYSTEMS ANALYSIS AND DESIGN, 11E. Expanded coverage of emerging technologies, such as agile methods, cloud computing, and mobile applications, complements this book's traditional approaches to systems analysis and design. A wealth of real-world examples throughout the book emphasizes critical thinking and IT skills in a dynamic, business-related environment. You will find numerous projects, insightful assignments, and helpful end-of-chapter exercises both within this edition and online. Detailed instructor support helps you effectively emphasize the IT skills your students need for success in today's intensely competitive business world.

Computer Organization and Design MIPS Edition, Fifth Edition: The Hardware/Software Interface (The Morgan Kaufmann Series in Computer Architecture and Design)

By David A. Patterson

Brand: Morgan Kaufmann
Paperback (800 pages)

Computer Organization and Design MIPS Edition, Fifth Edition: The Hardware/Software Interface (The Morgan Kaufmann Series in Computer Architecture and Design)
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Computer Organization and Design, Fifth Edition, is the latest update to the classic introduction to computer organization. The text now contains new examples and material highlighting the emergence of mobile computing and the cloud. It explores this generational change with updated content featuring tablet computers, cloud infrastructure, and the ARM (mobile computing devices) and x86 (cloud computing) architectures. The book uses a MIPS processor core to present the fundamentals of hardware technologies, assembly language, computer arithmetic, pipelining, memory hierarchies and I/O.Because an understanding of modern hardware is essential to achieving good performance and energy efficiency, this edition adds a new concrete example, Going Faster, used throughout the text to demonstrate extremely effective optimization techniques. There is also a new discussion of the Eight Great Ideas of computer architecture. Parallelism is examined in depth with examples and content highlighting parallel hardware and software topics. The book features the Intel Core i7, ARM Cortex-A8 and NVIDIA Fermi GPU as real-world examples, along with a full set of updated and improved exercises.

This new edition is an ideal resource for professional digital system designers, programmers, application developers, and system software developers. It will also be of interest to undergraduate students in Computer Science, Computer Engineering and Electrical Engineering courses in Computer Organization, Computer Design, ranging from Sophomore required courses to Senior Electives.

  • Winner of a 2014 Texty Award from the Text and Academic Authors Association
  • Includes new examples, exercises, and material highlighting the emergence of mobile computing and the cloud
  • Covers parallelism in depth with examples and content highlighting parallel hardware and software topics
  • Features the Intel Core i7, ARM Cortex-A8 and NVIDIA Fermi GPU as real-world examples throughout the book
  • Adds a new concrete example, "Going Faster," to demonstrate how understanding hardware can inspire software optimizations that improve performance by 200 times
  • Discusses and highlights the "Eight Great Ideas" of computer architecture:  Performance via Parallelism; Performance via Pipelining; Performance via Prediction; Design for Moore's Law; Hierarchy of Memories; Abstraction to Simplify Design; Make the Common Case Fast;  and Dependability via Redundancy
  • Includes a full set of updated and improved exercises

Control Systems Engineering

By Norman S. Nise

Wiley
Hardcover (944 pages)

Control Systems Engineering
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Control Systems Engineering, 7th Edition has become the top selling text for this course. It takes a practical approach, presenting clear and complete explanations. Real world examples demonstrate the analysis and design process, while helpful skill assessment exercises, numerous in-chapter examples, review  questions and problems reinforce key concepts. A new progressive problem, a solar energy  parabolic trough collector, is featured at the end of each chapter. This edition also includes  Hardware Interface Laboratory experiments for use on the MyDAQ platform from National Instruments. A tutorial for MyDAQ is included as Appendix D.




 
 



   

 
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