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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.
Number of Pages:696

Python Crash Course: A Hands-On, Project-Based Introduction to Programming

By Eric Matthes

No Starch Press
Released: 2015-11-01
Paperback (560 pages)

Python Crash Course: A Hands-On, Project-Based Introduction to Programming
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  • No Starch Press
Product Description:
Python Crash Course is a fast-paced, thorough introduction to Python that will have you writing programs, solving problems, and making things that work in no time.

In the first half of the book, you’ll learn about basic programming concepts, such as lists, dictionaries, classes, and loops, and practice writing clean and readable code with exercises for each topic. You’ll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you’ll put your new knowledge into practice with three substantial projects: a Space Invaders–inspired arcade game, data visualizations with Python’s super-handy libraries, and a simple web app you can deploy online.

As you work through Python Crash Course you’ll learn how to:
–Use powerful Python libraries and tools, including matplotlib, NumPy, and Pygal
–Make 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progresses
–Work with data to generate interactive visualizations
–Create and customize Web apps and deploy them safely online
–Deal with mistakes and errors so you can solve your own programming problems


If you’ve been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code!

Uses Python 2 and 3

Effective Java (3rd Edition)

By Joshua Bloch

Addison-Wesley Professional
Released: 2017-12-27
Paperback (416 pages)

Effective Java (3rd Edition)
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The Definitive Guide to Java Platform Best Practices–Updated for Java 7, 8, and 9

 

Java has changed dramatically since the previous edition of Effective Java was published shortly after the release of Java 6. This Jolt award-winning classic has now been thoroughly updated to take full advantage of the latest language and library features. The support in modern Java for multiple paradigms increases the need for specific best-practices advice, and this book delivers.

 

As in previous editions, each chapter of Effective Java, Third Edition, consists of several “items,” each presented in the form of a short, stand-alone essay that provides specific advice, insight into Java platform subtleties, and updated code examples. The comprehensive descriptions and explanations for each item illuminate what to do, what not to do, and why.

 

The third edition covers language and library features added in Java 7, 8, and 9, including the functional programming constructs that were added to its object-oriented roots. Many new items have been added, including a chapter devoted to lambdas and streams.

 

New coverage includes

  • Functional interfaces, lambda expressions, method references, and streams
  • Default and static methods in interfaces
  • Type inference, including the diamond operator for generic types
  • The @SafeVarargs annotation
  • The try-with-resources statement
  • New library features such as the Optional interface, java.time, and the convenience factory methods for collections


Web Design with HTML, CSS, JavaScript and jQuery Set

By Jon Duckett

Wiley
Paperback (1152 pages)

Web Design with HTML, CSS, JavaScript and jQuery Set
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  • Wiley
Product Description:
A two-book set for web designers and front-end developers

This two-book set combines the titles HTML & CSS: Designing and Building Web Sites and JavaScript & jQuery: Interactive Front-End Development. Together these two books form an ideal platform for anyone who wants to master HTML and CSS before stepping up to JavaScript and jQuery.

HTML & CSS covers structure, text, links, images, tables, forms, useful options, adding style with CSS, fonts, colors, thinking in boxes, styling lists and tables, layouts, grids, and even SEO, Google analytics, ftp, and HTML5. JavaScript & jQuery offers an excellent combined introduction to these two technologies using a clear and simple visual approach using diagrams, infographics, and photographs.

  • A handy two-book set that uniquely combines related technologies
  • Highly visual format and accessible language makes these books highly effective learning tools
  • Perfect for beginning web designers and front-end developers

Clean Code: A Handbook of Agile Software Craftsmanship

By Robert C. Martin

Prentice Hall
Released: 2008-08-01
Paperback (464 pages)

Clean Code: A Handbook of Agile Software Craftsmanship
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  • Prentice Hall
Product Description:
Even bad code can function. But if code isn’t clean, it can bring a development organization to its knees. Every year, countless hours and significant resources are lost because of poorly written code. But it doesn’t have to be that way.

Noted software expert Robert C. Martin presents a revolutionary paradigm with Clean Code: A Handbook of Agile Software Craftsmanship . Martin has teamed up with his colleagues from Object Mentor to distill their best agile practice of cleaning code “on the fly” into a book that will instill within you the values of a software craftsman and make you a better programmer—but only if you work at it.

What kind of work will you be doing? You’ll be reading code—lots of code. And you will be challenged to think about what’s right about that code, and what’s wrong with it. More importantly, you will be challenged to reassess your professional values and your commitment to your craft.

Clean Code is divided into three parts. The first describes the principles, patterns, and practices of writing clean code. The second part consists of several case studies of increasing complexity. Each case study is an exercise in cleaning up code—of transforming a code base that has some problems into one that is sound and efficient. The third part is the payoff: a single chapter containing a list of heuristics and “smells” gathered while creating the case studies. The result is a knowledge base that describes the way we think when we write, read, and clean code.

Readers will come away from this book understanding
  • How to tell the difference between good and bad code
  • How to write good code and how to transform bad code into good code
  • How to create good names, good functions, good objects, and good classes
  • How to format code for maximum readability
  • How to implement complete error handling without obscuring code logic
  • How to unit test and practice test-driven development
This book is a must for any developer, software engineer, project manager, team lead, or systems analyst with an interest in producing better code.

Automate the Boring Stuff with Python: Practical Programming for Total Beginners

By Al Sweigart

No Starch Press
Released: 2015-04-14
Paperback (504 pages)

Automate the Boring Stuff with Python: Practical Programming for Total Beginners
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Product Description:
If you’ve ever spent hours renaming files or updating hundreds of spreadsheet cells, you know how tedious tasks like these can be. But what if you could have your computer do them for you?

In Automate the Boring Stuff with Python, you’ll learn how to use Python to write programs that do in minutes what would take you hours to do by hand—no prior programming experience required. Once you’ve mastered the basics of programming, you’ll create Python programs that effortlessly perform useful and impressive feats of automation to:
–Search for text in a file or across multiple files
–Create, update, move, and rename files and folders
–Search the Web and download online content
–Update and format data in Excel spreadsheets of any size
–Split, merge, watermark, and encrypt PDFs
–Send reminder emails and text notifications
–Fill out online forms

Step-by-step instructions walk you through each program, and practice projects at the end of each chapter challenge you to improve those programs and use your newfound skills to automate similar tasks.

Don’t spend your time doing work a well-trained monkey could do. Even if you’ve never written a line of code, you can make your computer do the grunt work. Learn how in Automate the Boring Stuff with Python.

Note: The programs in this book are written to run on Python 3.

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

By Gareth James & Trevor Hastie

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.

Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

By Wes McKinney

O'Reilly Media
Paperback (544 pages)

Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
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  • Python for Data Analysis
  • 978-1491957660
  • Data Analysis
Product Description:

Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process.

Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.

  • Use the IPython shell and Jupyter notebook for exploratory computing
  • Learn basic and advanced features in NumPy (Numerical Python)
  • Get started with data analysis tools in the pandas library
  • Use flexible tools to load, clean, transform, merge, and reshape data
  • Create informative visualizations with matplotlib
  • Apply the pandas groupby facility to slice, dice, and summarize datasets
  • Analyze and manipulate regular and irregular time series data
  • Learn how to solve real-world data analysis problems with thorough, detailed examples

Adobe Photoshop CC Classroom in a Book (2018 release)

By Andrew Faulkner

Adobe Press
Paperback (400 pages)

Adobe Photoshop CC Classroom in a Book (2018 release)
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Creative professionals seeking the fastest, easiest, most comprehensive way to learn Adobe Photoshop choose Adobe Photoshop CC Classroom in a Book (2018 release) from Adobe Press. The 15 project-based lessons show key step-by-step techniques for working in Photoshop, including how to correct, enhance, and distort digital images, create image composites, and prepare images for print and the web.

 

In addition to learning the essential elements of the Photoshop interface, this revised edition for the 2018 release covers features like search capabilities, Content-Aware Crop, Select and Mask, Face-Aware Liquify, designing with multiple artboards, creating and organizing enhanced brush presets, and much more!

 

The online companion files include all the necessary assets for readers to complete the projects featured in each chapter as well as ebook updates when Adobe releases relevant new features for Creative Cloud customers. All buyers of the book get full access to the Web Edition: a Web-based version of the complete ebook enhanced with video and multiple-choice quizzes. 

Deep Learning with Python

By Francois Chollet

Manning Publications
Paperback (384 pages)

Deep Learning with Python
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Summary

Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the Technology

Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications.

About the Book

Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects.

What's Inside

  • Deep learning from first principles
  • Setting up your own deep-learning environment
  • Image-classification models
  • Deep learning for text and sequences
  • Neural style transfer, text generation, and image generation

About the Reader

Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required.

About the Author

François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others.

Table of Contents

    PART 1 - FUNDAMENTALS OF DEEP LEARNING

  1. What is deep learning?
  2. Before we begin: the mathematical building blocks of neural networks
  3. Getting started with neural networks
  4. Fundamentals of machine learning
  5. PART 2 - DEEP LEARNING IN PRACTICE

  6. Deep learning for computer vision
  7. Deep learning for text and sequences
  8. Advanced deep-learning best practices
  9. Generative deep learning
  10. Conclusions
  11. appendix A - Installing Keras and its dependencies on Ubuntu
  12. appendix B - Running Jupyter notebooks on an EC2 GPU instance



 
 



   

 
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