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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

Ethereum: Blockchains, Digital Assets, Smart Contracts, Decentralized Autonomous Organizations

By Henning Diedrich

CreateSpace Independent Publishing Platform
Paperback (360 pages)

Ethereum: Blockchains, Digital Assets, Smart Contracts, Decentralized Autonomous Organizations
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Blockchain For the Non-Technical

*** THIS IS A PREVIEW PRINT ***

As IBM´s official liaison to the Ethereum core developers I gave talks on blockchain topics pretty much around the world. After one keynote I was asked for a non-technical guide to understand blockchains. This is it.

The book aims to help you get your head around blockchains in general and around Ethereum specifically. Since Ethereum is currently the pre-imminent blockchain, it makes sense as reference point. The essential stuff is the same for any blockchain.

This text was written for people with a fast grasp, who are not programmers. Reading this should give you the basics to cut through the hype and to identify blockchain opportunities in your professional domain. There are tiny bits of code, which can be admired and skipped.

We´ll look at Ethereum´s benefits first, how it is used and what can be done with it; then explain blockchain machinery, visiting the terms that you´ll be confronted with in every discussion about its application. Exactly what you need to tell the signal from the noise in the echo chamber of honest misunderstandings and desperate marketing.

We take a good hard look at limitations, throw in some history and names and give a realistic outlook.

The index reads like an FAQ and you can use the book like that. However, there is a strong build up, one chapter leading to the next, as optimized path to understanding all the interconnected, moving parts. There´s quite a number of them.

Blockchains are not a trivial topic. The fact that blockchain client programs are small has fooled many people into believing it can´t possibly be that hard. The challenges are in the implications though.

But what’s in this book will put you ahead of almost everyone outside the core bubble.

A deep dive into this field now – at least getting started – will help you to become part of the fun ahead. It should allow you to stand out, land deals or a great job.

It will also make you see first hand how early we are in the game.

Hopefully, we will find a contributor to the blockchain community in you, strengthening the portfolio of real-world use cases. Ideally, you´ll learn to navigate your own uncharted course through your domain and revolutionize it.

From the Book’s Index:

What is Ethereum?
What is Ether?
What is Ethereum Not?
What is Ethereum Used for?
Create Your Own Digital Currency!
How Does Ethereum Compare?
How Does Ethereum Work?

What is a Blockchain?
What is Cryptography?
What´s the Magic?
What is Holding It Back?
What is a Cryptocurrency?
What is a Digital Currency?
What is a Digital Asset?
What is a Mirror Asset?
What is Consensus?
What is Proof–of–Work?
What is Proof–of–Stake?
What is a Hard–Fork?
What is Mining?
What is Decentralized Code?
What is a Decentralized Application (Dapp)?
What is a Smart Contract?
What is a Decentralized Autonomous Organization (DAO)?
What is an Oracle?
What is Timestamping?
What is a Private Chain?
What is the EVM?
What is Gas?
What is Solidity?

How Fast is Ethereum / Latency?
What is Ethereum´s Capacity / Throughput?
What is Probabilistic Finality?
How Ready is Ethereum?
Is Ethereum Legal?

How did Bitcoin Start?
What’s the Story Behind Ethereum?
What is The DAO?
What is Ethereum Classic?
What is all the Hype about?
What’s the Future?
Will Ethereum Change the World?

APPENDIX with technical notes
Hello, World!
Installation
Clients

Drafts of the book have been run by core Ethereum people and highest ranking IBM engineers in a bid to ensure accuracy.

I’ll be happy to hear what you felt was missing or presented out of order, no matter your background.

Opinions in this book are mine, not that of IBM.

I am not an Ethereum spokesperson either.

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. 

Head First Java, 2nd Edition

By Kathy Sierra

Sierra, Kathy/ Bates, Bert
Released: 2005-02-09
Paperback (688 pages)

Head First Java, 2nd Edition
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  • O'Reilly Media
Product Description:

Learning a complex new language is no easy task especially when it s an object-oriented computer programming language like Java. You might think the problem is your brain. It seems to have a mind of its own, a mind that doesn't always want to take in the dry, technical stuff you're forced to study.

The fact is your brain craves novelty. It's constantly searching, scanning, waiting for something unusual to happen. After all, that's the way it was built to help you stay alive. It takes all the routine, ordinary, dull stuff and filters it to the background so it won't interfere with your brain's real work--recording things that matter. How does your brain know what matters? It's like the creators of the Head First approach say, suppose you're out for a hike and a tiger jumps in front of you, what happens in your brain? Neurons fire. Emotions crank up. Chemicals surge. That's how your brain knows.

And that's how your brain will learn Java. Head First Java combines puzzles, strong visuals, mysteries, and soul-searching interviews with famous Java objects to engage you in many different ways. It's fast, it's fun, and it's effective. And, despite its playful appearance, Head First Java is serious stuff: a complete introduction to object-oriented programming and Java. You'll learn everything from the fundamentals to advanced topics, including threads, network sockets, and distributed programming with RMI. And the new. second edition focuses on Java 5.0, the latest version of the Java language and development platform. Because Java 5.0 is a major update to the platform, with deep, code-level changes, even more careful study and implementation is required. So learning the Head First way is more important than ever.

If you've read a Head First book, you know what to expect--a visually rich format designed for the way your brain works. If you haven't, you're in for a treat. You'll see why people say it's unlike any other Java book you've ever read.

By exploiting how your brain works, Head First Java compresses the time it takes to learn and retain--complex information. Its unique approach not only shows you what you need to know about Java syntax, it teaches you to think like a Java programmer. If you want to be bored, buy some other book. But if you want to understand Java, this book's for you.

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.

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

By Trevor Hastie & Jerome Friedman

imusti
Hardcover (745 pages)

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
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  • Springer
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This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing 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 colour graphics. It is 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.

This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorisation, and spectral clustering. There is also a chapter on methods for "wide'' data (p bigger than n), including multiple testing and false discovery rates.

Irresistible: The Rise of Addictive Technology and the Business of Keeping Us Hooked

By Adam Alter

PENGUIN PRESS
Released: 2017-03-07
Hardcover (368 pages)

Irresistible: The Rise of Addictive Technology and the Business of Keeping Us Hooked
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  • PENGUIN PRESS
Product Description:
“One of the most mesmerizing and important books I’ve read in quite some time. Alter brilliantly illuminates the new obsessions that are controlling our lives and offers the tools we need to rescue our businesses, our families, and our sanity.” Adam Grant, New York Times bestselling author of Originals and Give and Take

Welcome to the age of behavioral addiction—an age in which half of the American population is addicted to at least one behavior. We obsess over our emails, Instagram likes, and Facebook feeds; we binge on TV episodes and YouTube videos; we work longer hours each year; and we spend an average of three hours each day using our smartphones. Half of us would rather suffer a broken bone than a broken phone, and Millennial kids spend so much time in front of screens that they struggle to interact with real, live humans.
 
In this revolutionary book, Adam Alter, a professor of psychology and marketing at NYU, tracks the rise of behavioral addiction, and explains why so many of today's products are irresistible. Though these miraculous products melt the miles that separate people across the globe, their extraordinary and sometimes damaging magnetism is no accident. The companies that design these products tweak them over time until they become almost impossible to resist.
 
By reverse engineering behavioral addiction, Alter explains how we can harness addictive products for the good—to improve how we communicate with each other, spend and save our money, and set boundaries between work and play—and how we can mitigate their most damaging effects on our well-being, and the health and happiness of our children.

Adam Alter's previous book, Drunk Tank Pink: And Other Unexpected Forces that Shape How We Think, Feel, and Behave is available in paperback from Penguin.

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
Product Description:

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.




 
 



   

 
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