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WildComputer.com > Books > Computer Science

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Cracking the Coding Interview: 189 Programming Questions and Solutions

By Gayle Laakmann McDowell

CareerCup
Released: 2015-07-01
Paperback (706 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.
Number of Pages:696

CompTIA A+ Certification All-in-One Exam Guide, Tenth Edition (Exams 220-1001 & 220-1002)

By Mike Meyers

McGraw-Hill Education
Released: 2019-04-12
Hardcover (1568 pages)

CompTIA A+ Certification All-in-One Exam Guide, Tenth Edition (Exams 220-1001 & 220-1002)
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Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.

This bestselling on-the-job reference and test preparation guide has been fully revised for the new 2019 CompTIA Core 1 and Core 2 CompTIA A+ exam objectives

This fully revised and updated resource offers complete coverage of the latest release of CompTIA A+ exams 220-1001 & 220-1002. You'll find learning objectives at the beginning of each chapter, exam tips, practice exam questions, and in-depth explanations. Designed to help you pass the CompTIA A+ exams with ease, this definitive guide also serves as an essential on-the-job IT reference.

Covers all exam topics, including how to:

Work with CPUs, RAM, BIOS, motherboards, power supplies, and other personal computer components
Install, configure, and maintain hard drives
Manage input devices and removable media
Set up, upgrade, and maintain all versions of Windows
Troubleshoot and fix computer problems
Install printers and other peripherals
Configure and secure mobile devices
Connect to the Internet
Set up wired and wireless networks
Protect your personal computer and your network
Implement virtualization and cloud-based technologies

Online content includes:

Practice exams for 1001 & 1002
More than one hour of free video training
TotalSim simulations of performance-based questions
Mike Meyers’ favorite PC tools and utilities




Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again

By Eric Topol

Basic Books
Released: 2019-03-12
Hardcover (400 pages)

Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again
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One of America's top doctors reveals how AI will empower physicians and revolutionize patient care

Medicine has become inhuman, to disastrous effect. The doctor-patient relationship--the heart of medicine--is broken: doctors are too distracted and overwhelmed to truly connect with their patients, and medical errors and misdiagnoses abound. In Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help. AI has the potential to transform everything doctors do, from notetaking and medical scans to diagnosis and treatment, greatly cutting down the cost of medicine and reducing human mortality. By freeing physicians from the tasks that interfere with human connection, AI will create space for the real healing that takes place between a doctor who can listen and a patient who needs to be heard.

Innovative, provocative, and hopeful, Deep Medicine shows us how the awesome power of AI can make medicine better, for all the humans involved.

Barron's AP Computer Science A with Online Tests

By Roselyn Teukolsky M.S.

Barron s Educational Series Inc U S
Released: 2018-01-01
Paperback (528 pages)

Barron s AP Computer Science A with Online Tests
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  • Barron s Educational Series Inc U S
Product Description:
Barron’s AP Computer Science A with Online Tests is aligned with the current exam curriculum and provides key practice and subject review. This edition reflects the removal of the ClassCastException and downcasting from the AP Java subset, and practice tests include the free-response style used on recent exams.

This edition includes:
  • Two-full length practice tests in the book
  • Three additional full-length practice tests online
  • A diagnostic test to pinpoint strengths and weaknesses so students can focus on areas where they need more study
  • Answers and explanations for every test question
  • Charts detailing the scoring suggestions for each free-response question

The content review includes static variables, the List interface, enhanced for loops, the import statement, many questions on 2-dimensional arrays, and a detailed analysis of the binary search algorithm.

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

By Aurélien Géron

O'Reilly Media
Released: 2017-04-09
Paperback (574 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

The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power

By Shoshana Zuboff

PublicAffairs
Released: 2019-01-15
Hardcover (704 pages)

The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power
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The challenges to humanity posed by the digital future, the first detailed examination of the unprecedented form of power called "surveillance capitalism," and the quest by powerful corporations to predict and control our behavior.

In this masterwork of original thinking and research, Shoshana Zuboff provides startling insights into the phenomenon that she has named surveillance capitalism. The stakes could not be higher: a global architecture of behavior modification threatens human nature in the twenty-first century just as industrial capitalism disfigured the natural world in the twentieth.

Zuboff vividly brings to life the consequences as surveillance capitalism advances from Silicon Valley into every economic sector. Vast wealth and power are accumulated in ominous new "behavioral futures markets," where predictions about our behavior are bought and sold, and the production of goods and services is subordinated to a new "means of behavioral modification."

The threat has shifted from a totalitarian Big Brother state to a ubiquitous digital architecture: a "Big Other" operating in the interests of surveillance capital. Here is the crucible of an unprecedented form of power marked by extreme concentrations of knowledge and free from democratic oversight. Zuboff's comprehensive and moving analysis lays bare the threats to twenty-first century society: a controlled "hive" of total connection that seduces with promises of total certainty for maximum profit--at the expense of democracy, freedom, and our human future.

With little resistance from law or society, surveillance capitalism is on the verge of dominating the social order and shaping the digital future--if we let it.

Deep Learning (Adaptive Computation and Machine Learning series)

By Ian Goodfellow & Aaron Courville

The MIT Press
Released: 2016-11-18
Hardcover (775 pages)

Deep Learning (Adaptive Computation and Machine Learning series)
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  • deep learning adaptive computation and machine learning series
Product Description:

An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.

“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.

The Hundred-Page Machine Learning Book

By Andriy Burkov

Andriy Burkov
Paperback (159 pages)

The Hundred-Page Machine Learning Book
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Peter Norvig, Research Director at Google, co-author of AIMA, the most popular AI textbook in the world: "Burkov has undertaken a very useful but impossibly hard task in reducing all of machine learning to 100 pages. He succeeds well in choosing the topics — both theory and practice — that will be useful to practitioners, and for the reader who understands that this is the first 100 (or actually 150) pages you will read, not the last, provides a solid introduction to the field."

Aurélien Géron, Senior AI Engineer, author of the bestseller Hands-On Machine Learning with Scikit-Learn and TensorFlow: "The breadth of topics the book covers is amazing for just 100 pages (plus few bonus pages!). Burkov doesn't hesitate to go into the math equations: that's one thing that short books usually drop. I really liked how the author explains the core concepts in just a few words. The book can be very useful for newcomers in the field, as well as for old-timers who can gain from such a broad view of the field."

Karolis Urbonas, Head of Data Science at Amazon: "A great introduction to machine learning from a world-class practitioner."

Chao Han, VP, Head of R&D at Lucidworks: "I wish such a book existed when I was a statistics graduate student trying to learn about machine learning."

Sujeet Varakhedi, Head of Engineering at eBay: "Andriy's book does a fantastic job of cutting the noise and hitting the tracks and full speed from the first page.''

Deepak Agarwal, VP of Artificial Intelligence at LinkedIn: "A wonderful book for engineers who want to incorporate ML in their day-to-day work without necessarily spending an enormous amount of time.''

Vincent Pollet, Head of Research at Nuance: "The Hundred-Page Machine Learning Book is an excellent read to get started with Machine Learning.''

Everything you really need to know in Machine Learning in a hundred pages.

This is the first of its kind "read first, buy later" book. You can find the book online, read it, and then come back to pay for it if you liked the book or found it useful for your work, business or studies.

AI Superpowers: China, Silicon Valley, and the New World Order

By Kai-Fu Lee

Houghton Mifflin Harcourt
Released: 2018-09-25
Hardcover (272 pages)

AI Superpowers: China, Silicon Valley, and the New World Order
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THE NEW YORK TIMES, USA TODAY, AND WALL STREET JOURNAL BESTSELLER

Dr. Kai-Fu Lee—one of the world’s most respected experts on AI and China—reveals that China has suddenly caught up to the US at an astonishingly rapid and unexpected pace.  

In AI Superpowers, Kai-fu Lee argues powerfully that because of these unprecedented developments in AI, dramatic changes will be happening much sooner than many of us expected. Indeed, as the US-Sino AI competition begins to heat up, Lee urges the US and China to both accept and to embrace the great responsibilities that come with significant technological power. Most experts already say that AI will have a devastating impact on blue-collar jobs. But Lee predicts that Chinese and American AI will have a strong impact on white-collar jobs as well. Is universal basic income the solution? In Lee’s opinion, probably not.  But he provides  a clear description of which jobs will be affected and how soon, which jobs can be enhanced with AI, and most importantly, how we can provide solutions to some of the most profound changes in human history that are coming soon.

The Simulation Hypothesis: An MIT Computer Scientist Shows Why AI, Quantum Physics and Eastern Mystics All Agree We Are In a Video Game

By Rizwan Virk

Bayview Books
Paperback (324 pages)

The Simulation Hypothesis: An MIT Computer Scientist Shows Why AI, Quantum Physics and Eastern Mystics All Agree We Are In a Video Game
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Written by well-known Silicon Valley entrepreneur and MIT-educated computer scientist Rizwan Virk, The Simulation Hypothesis brings together disparate fields to explore one of the most daring and consequential theories of our time: The Simulation Hypothesis. Whether you are a computer scientist, a fan of science fiction like the Matrix movies, a video game enthusiast, or a spiritual seeker, The Simulation Hypothesis touches on all these areas. The Simulation Hypothesis is the idea that our physical reality, far from being a solid physical universe, is part of an increasingly sophisticated video game-like simulation, consisting of pixels with its own internal clock.In the Simulation Hypothesis, the mysteries of quantum science, the path of artificially intelligent consciousness, the evolution of VR and quantum computers, along with previously taboo subjects like consciousness and karma, are brought together into a cohesive, information-based computer science framework. Leading figures like Elon Musk and Stephen Hawking have advocated the Simulation Hypothesis. For the first time, the Simulation Hypothesis delves into all the angles that make this remarkable theory one of the most important of our time!

This book lays out both the technical aspects of computer simulation and the mystical reasons why we can take Philip K. Dick seriously when he proposed that we are living in a computer-generated reality. His vision that this world is not quite real informed much of his science fiction. This book explains that idea from scientific and religious perspectives. --Tessa B. Dick, author of Conversations with Philip K. Dick

The Simulation Hypothesis presents a radical alternative to current models of reality ... Many fields of human experience rejected or neglected by modern science can be brought under the framework proposed by Riz Virk, relying on the latest insights of computer science and on the author's unique experience with the design of digital games. The result is a stunning reappraisal of what it means to be human in an infinite universe. - --Jacques Vallée, venture capitalist and author of Forbidden Science.



 
 



   

 
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