Before you buy this book, please first head over to our sample page - elementsofprogramminginterviews.com/sample The sampler should give you a very good idea of the quality and style of our book. In particular, be sure you are comfortable with the level and with our Java coding style. Complete programs are available at epibook.github.io. Since different candidates have different time constraints, EPI includes a study guide with several scenarios, ranging from weekend Hackathon to semester long preparation with a recommended a subset of problems for each scenario. All problems are classified in terms of their difficulty level and include many variants to help you apply what you have learned more widely. All problems includes hints for readers who get stuck. This simulates what you will face in the real interview. The version being sold by Amazon itself is always current. Some resellers may have older versions, especially if they sell used copies. Table of Contents Part I The Interview Chapter 1 Getting Ready Chapter 2 Strategies For A Great Interview Chapter 3 Conducting An Interview Chapter 4 ProblemSolving Part II Problems Chapter 5 Primitive Types Chapter 6 Arrays Chapter 7 Strings Chapter 8 Linked Lists Chapter 9 Stacks and Queues Chapter 10 Binary Trees Chapter 11 Heaps Chapter 12 Searching Chapter 13 Hash Tables Chapter 14 Sorting Chapter 15 Binary Search Trees Chapter 16 Recursion Chapter 17 Dynamic Programming Chapter 18 Greedy Algorithms and Invariants Chapter 19 Graphs Chapter 20 Parallel Computing Part III Domain Specific Problems Chapter 21 Design Problems Chapter 22 Language Questions Chapter 23 Object-Oriented Design Chapter 24 Common Tools Part IV The Honors Class Chapter 25 Honors Class Part V Notation, and Index

1. 英文版，共1628页；不是中文版，不是中文版 2. 车载以太网的权威资料

Produce a fully functioning Intelligent System that leverages machine learning and data from user interactions to improve over time and achieve success. This book teaches you how to build an Intelligent System from end to end and leverage machine learning in practice. You will understand how to apply your existing skills in software engineering, data science, machine learning, management, and program management to produce working systems. Building Intelligent Systems is based on more than a decade of experience building Internet-scale Intelligent Systems that have hundreds of millions of user interactions per day in some of the largest and most important software systems in the world. What You'll Learn Understand the concept of an Intelligent System: What it is good for, when you need one, and how to set it up for success Design an intelligent user experience: Achieve your objectives and produce data to help make the Intelligent System better over time Implement an Intelligent System: Execute, manage, and measure Intelligent Systems in practice Create intelligence: Use different approaches, including machine learning Orchestrate an Intelligent System: Bring the parts together throughout its life cycle and achieve the impact you want This Book Is For Software engineers, machine learning practitioners, and technical managers who want to build effective intelligent systems. Table of Contents Part I: Approaching an Intelligent Systems Project Chapter 1: Introducing Intelligent Systems Chapter 2: Knowing When to Use Intelligent Systems Chapter 3: A Brief Refresher on Working with Data Chapter 4: Defining the Intelligent System’s Goals Part II: Intelligent Experiences Chapter 5: The Components of Intelligent Experiences Chapter 6: Why Creating Intelligent Experiences Is Hard Chapter 7: Balancing Intelligent Experiences Chapter 8: Modes of Intelligent Interaction Chapter 9: Getting Data from Experience Chapter 10: Verifying Intelligent Experiences Part III: Implement