*How to Think Like a Computer Scientist*

Author: Allen B. Downey,Chris Mayfield

Publisher: "O'Reilly Media, Inc."

ISBN: 1491929510

Category: Computers

Page: 252

View: 9770

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## Think Java

Currently used at many colleges, universities, and high schools, this hands-on introduction to computer science is ideal for people with little or no programming experience. The goal of this concise book is not just to teach you Java, but to help you think like a computer scientist. You’ll learn how to program—a useful skill by itself—but you’ll also discover how to use programming as a means to an end. Authors Allen Downey and Chris Mayfield start with the most basic concepts and gradually move into topics that are more complex, such as recursion and object-oriented programming. Each brief chapter covers the material for one week of a college course and includes exercises to help you practice what you’ve learned. Learn one concept at a time: tackle complex topics in a series of small steps with examples Understand how to formulate problems, think creatively about solutions, and write programs clearly and accurately Determine which development techniques work best for you, and practice the important skill of debugging Learn relationships among input and output, decisions and loops, classes and methods, strings and arrays Work on exercises involving word games, graphics, puzzles, and playing cards
## Think Java

Currently used at many colleges, universities, and high schools, this hands-on introduction to computer science is ideal for people with little or no programming experience. The goal of this concise book is not just to teach you Java, but to help you think like a computer scientist. You’ll learn how to program—a useful skill by itself—but you’ll also discover how to use programming as a means to an end. Authors Allen Downey and Chris Mayfield start with the most basic concepts and gradually move into topics that are more complex, such as recursion and object-oriented programming. Each brief chapter covers the material for one week of a college course and includes exercises to help you practice what you’ve learned. Learn one concept at a time: tackle complex topics in a series of small steps with examples Understand how to formulate problems, think creatively about solutions, and write programs clearly and accurately Determine which development techniques work best for you, and practice the important skill of debugging Learn relationships among input and output, decisions and loops, classes and methods, strings and arrays Work on exercises involving word games, graphics, puzzles, and playing cards
## HT THINK LIKE A COMPUTER SCIEN

The goal of this book is to teach you to think like a computer scientist. This way of thinking combines some of the best features of mathematics, engineering, and natural science. Like mathematicians, computer scientists use formal languages to denote ideas (specifically computations). Like engineers, they design things, assembling components into systems and evaluating tradeoffs among alternatives. Like scientists, they observe the behavior of complex systems, form hypotheses, and test predictions. The single most important skill for a computer scientist is problem solving. Problem solving means the ability to formulate problems, think creatively about solutions, and express a solution clearly and accurately. As it turns out, the process of learning to program is an excellent opportunity to practice problem-solving skills. That's why this chapter is called, The way of the program. On one level, you will be learning to program, a useful skill by itself. On another level, you will use programming as a means to an end. As we go along, that end will become clearer.
## Think Perl 6

Want to learn how to program and think like a computer scientist? This practical guide gets you started on your programming journey with the help of Perl 6, the younger sister of the popular Perl programming language. Ideal for beginners, this hands-on book includes over 100 exercises with multiple solutions, and more than 1,000 code examples so you can quickly practice what you learn. Experienced programmers—especially those who know Perl 5—will also benefit. Divided into two parts, Think Perl 6 starts with basic concepts that every programmer needs to know, and then focuses on different programming paradigms and some more advanced programming techniques. With two semesters’ worth of lessons, this book is the perfect teaching tool for computer science beginners in colleges and universities. Learn basic concepts including variables, expressions, statements, functions, conditionals, recursion, and loops Understand commonly used basic data structures and the most useful algorithms Dive into object-oriented programming, and learn how to construct your own types and methods to extend the language Use grammars and regular expressions to analyze textual content Explore how functional programming can help you make your code simpler and more expressive
## Think Python

If you want to learn how to program, working with Python is an excellent way to start. This hands-on guide takes you through the language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. This second edition and its supporting code have been updated for Python 3. Through exercises in each chapter, you’ll try out programming concepts as you learn them. Think Python is ideal for students at the high school or college level, as well as self-learners, home-schooled students, and professionals who need to learn programming basics. Beginners just getting their feet wet will learn how to start with Python in a browser. Start with the basics, including language syntax and semantics Get a clear definition of each programming concept Learn about values, variables, statements, functions, and data structures in a logical progression Discover how to work with files and databases Understand objects, methods, and object-oriented programming Use debugging techniques to fix syntax, runtime, and semantic errors Explore interface design, data structures, and GUI-based programs through case studies
## Think Data Structures

If you're a student studying computer science or a software developer preparing for technical interviews, this practical book will help you learn and review some of the most important ideas in software engineering--data structures and algorithms--in a way that's clearer, more concise, and more engaging than other materials. By emphasizing practical knowledge and skills over theory, author Allen Downey shows you how to use data structures to implement efficient algorithms, and then analyze and measure their performance. You'll explore the important classes in the Java collections framework (JCF), how they're implemented, and how they're expected to perform. Each chapter presents hands-on exercises supported by test code online. Use data structures such as lists and maps, and understand how they work Build an application that reads Wikipedia pages, parses the contents, and navigates the resulting data tree Analyze code to predict how fast it will run and how much memory it will require Write classes that implement the Map interface, using a hash table and binary search tree Build a simple web search engine with a crawler, an indexer that stores web page contents, and a retriever that returns user query results Other books by Allen Downey include Think Java, Think Python, Think Stats, and Think Bayes.
## Python for Software Design

Python for Software Design is a concise introduction to software design using the Python programming language. The focus is on the programming process, with special emphasis on debugging. The book includes a wide range of exercises, from short examples to substantial projects, so that students have ample opportunity to practice each new concept.
## Think Stats

If you know how to program, you have the skills to turn data into knowledge, using tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python. By working with a single case study throughout this thoroughly revised book, you’ll learn the entire process of exploratory data analysis—from collecting data and generating statistics to identifying patterns and testing hypotheses. You’ll explore distributions, rules of probability, visualization, and many other tools and concepts. New chapters on regression, time series analysis, survival analysis, and analytic methods will enrich your discoveries. Develop an understanding of probability and statistics by writing and testing code Run experiments to test statistical behavior, such as generating samples from several distributions Use simulations to understand concepts that are hard to grasp mathematically Import data from most sources with Python, rather than rely on data that’s cleaned and formatted for statistics tools Use statistical inference to answer questions about real-world data
## Think Complexity

Complexity science uses computation to explore the physical and social sciences. In Think Complexity, you’ll use graphs, cellular automata, and agent-based models to study topics in physics, biology, and economics. Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of worked examples, exercises, case studies, and easy-to-understand explanations. In this updated second edition, you will: Work with NumPy arrays and SciPy methods, including basic signal processing and Fast Fourier Transform Study abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machines Get Jupyter notebooks filled with starter code and solutions to help you re-implement and extend original experiments in complexity; and models of computation like Turmites, Turing machines, and cellular automata Explore the philosophy of science, including the nature of scientific laws, theory choice, and realism and instrumentalism Ideal as a text for a course on computational modeling in Python, Think Complexity also helps self-learners gain valuable experience with topics and ideas they might not encounter otherwise.
## Think Like a Programmer

The real challenge of programming isn't learning a language's syntax—it's learning to creatively solve problems so you can build something great. In this one-of-a-kind text, author V. Anton Spraul breaks down the ways that programmers solve problems and teaches you what other introductory books often ignore: how to Think Like a Programmer. Each chapter tackles a single programming concept, like classes, pointers, and recursion, and open-ended exercises throughout challenge you to apply your knowledge. You'll also learn how to: –Split problems into discrete components to make them easier to solve –Make the most of code reuse with functions, classes, and libraries –Pick the perfect data structure for a particular job –Master more advanced programming tools like recursion and dynamic memory –Organize your thoughts and develop strategies to tackle particular types of problems Although the book's examples are written in C++, the creative problem-solving concepts they illustrate go beyond any particular language; in fact, they often reach outside the realm of computer science. As the most skillful programmers know, writing great code is a creative art—and the first step in creating your masterpiece is learning to Think Like a Programmer.
## Thinking in Java

With humor and insight, the author introduces the fundamental concepts of the Java programming language, from object development to design patterns, with the help of straightforward examples. By the author of Thinking in C++++. Original. (Beginner).
## Introduction to Programming in Java

This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Programming skills are indispensable in today’s world, not just for computer science students, but also for anyone in any scientific or technical discipline. Introduction to Programming in Java, Second Edition, by Robert Sedgewick and Kevin Wayne is an accessible, interdisciplinary treatment that emphasizes important and engaging applications, not toy problems. The authors supply the tools needed for students and professionals to learn that programming is a natural, satisfying, and creative experience, and to become conversant with one of the world’s most widely used languages. This example-driven guide focuses on Java’s most useful features and brings programming to life for every student in the sciences, engineering, and computer science. Coverage includes Basic elements of programming: variables, assignment statements, built-in data types, conditionals, loops, arrays, and I/O, including graphics and sound Functions, modules, and libraries: organizing programs into components that can be independently debugged, maintained, and reused Algorithms and data structures: sort/search algorithms, stacks, queues, and symbol tables Applications from applied math, physics, chemistry, biology, and computer science Drawing on their extensive classroom experience, throughout the text the authors provide Q&As, exercises, and opportunities for creative engagement with the material. Together with the companion materials described below, this book empowers people to pursue a modern approach to teaching and learning programming. Companion web site (introcs.cs.princeton.edu/java) contains Chapter summaries Supplementary exercises, some with solutions Detailed instructions for installing a Java programming environment Program code and test data suitable for easy download Detailed creative exercises, projects, and other supplementary materials Companion studio-produced online videos (informit.com/sedgewick) are available for purchase and provide students and professionals with the opportunity to engage with the material at their own pace and give instructors the opportunity to spend their time with students helping them to succeed on assignments and exams. Register your product at informit.com/register for convenient access to downloads, updates, and corrections as they become available.
## Physical Modeling in MATLAB

An introductory textbook for people who have not programmed before. Covers basic MATLAB programming with emphasis on modeling and simulation of physical systems.
## Think Bayes

If you know how to program with Python and also know a little about probability, you’re ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical notation, and use discrete probability distributions instead of continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer, and you’ll begin to apply these techniques to real-world problems. Bayesian statistical methods are becoming more common and more important, but not many resources are available to help beginners. Based on undergraduate classes taught by author Allen Downey, this book’s computational approach helps you get a solid start. Use your existing programming skills to learn and understand Bayesian statistics Work with problems involving estimation, prediction, decision analysis, evidence, and hypothesis testing Get started with simple examples, using coins, M&Ms, Dungeons & Dragons dice, paintball, and hockey Learn computational methods for solving real-world problems, such as interpreting SAT scores, simulating kidney tumors, and modeling the human microbiome.
## Blue Pelican Java

"Blue Pelican Java" is a somewhat unusual high school computer science textbook. Most computer science texts will begin with a section on the history of computers followed with a flurry of definitions that are just "so many words" to the average student. The approach here is to first give the student some experience upon which to hang the definitions that come later. The usual practice of introducing classes and objects is deferred until the student has a firm grasp of the fundamentals (loops, decision structures, etc). Thus, the beginning student is not overwhelmed by the simultaneous introduction of OOPs and the fundamentals. The book includes plenty of exercises (many in "contest" form), programming projects, and a huge appendix.
## What If?

The creator of the incredibly popular webcomic xkcd presents his heavily researched answers to his fans' oddest questions, including “What if I took a swim in a spent-nuclear-fuel pool?” and “Could you build a jetpack using downward-firing machine guns?” 100,000 first printing.
## What's New in Java 7

Java 7 has a number of features that will please developers. Madhusudhan Konda provides an overview of these, including strings in switch statements, multi-catch exception handling, try-with-resource statements, the new File System API, extensions of the JVM, support for dynamically-typed languages, and the fork and join framework for task parallelism.
## Think DSP

If you understand basic mathematics and know how to program with Python, you’re ready to dive into signal processing. While most resources start with theory to teach this complex subject, this practical book introduces techniques by showing you how they’re applied in the real world. In the first chapter alone, you’ll be able to decompose a sound into its harmonics, modify the harmonics, and generate new sounds. Author Allen Downey explains techniques such as spectral decomposition, filtering, convolution, and the Fast Fourier Transform. This book also provides exercises and code examples to help you understand the material. You’ll explore: Periodic signals and their spectrums Harmonic structure of simple waveforms Chirps and other sounds whose spectrum changes over time Noise signals and natural sources of noise The autocorrelation function for estimating pitch The discrete cosine transform (DCT) for compression The Fast Fourier Transform for spectral analysis Relating operations in time to filters in the frequency domain Linear time-invariant (LTI) system theory Amplitude modulation (AM) used in radio Other books in this series include Think Stats and Think Bayes, also by Allen Downey.
## Think Like a Data Scientist

Data science is more than just a set of tools and techniques for extracting knowledge from data sets and data streams. Data science is also a process of getting from goals and questions to real, valuable outcomes by exploring, observing, and manipulating a world of data. Traversing this world can be difficult and confusing. Software developers and non-technical folks may struggle with the uncertainty and fuzzy answers that data invariably provide, and statisticians may have trouble working with any of the multitude of relevant software tools that lie outside of their expertise. Others may not even know where to begin. Think Like a Data Scientist presents a step-by-step approach to data science, combining analytic, programming, and business perspectives into easy-to-digest techniques and thought processes for solving real world data-centric problems. This book helps you fill in conceptual knowledge gaps in the daunting fields of statistics and software development, and relates those skills to the real concerns of data science in the business world. As you work though the many practical examples, you'll use your existing knowledge of statistics and programming to solve real problems in data science. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

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*How to Think Like a Computer Scientist*

Author: Allen B. Downey,Chris Mayfield

Publisher: "O'Reilly Media, Inc."

ISBN: 1491929510

Category: Computers

Page: 252

View: 9770

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Publisher: "O'Reilly Media, Inc."

ISBN: 1491929537

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