Top PDF How to Think Like a Computer Scientist: C++ Version

How to Think Like a Computer Scientist: C++ Version

How to Think Like a Computer Scientist: C++ Version

The goal of this book is to teach you to think like a computer scientist. I like the way computer scientists think because they combine some of the best fea- tures of Mathematics, Engineering, and Natural Science. Like mathematicians, computer scientists use formal languages to denote ideas (specifically computa- tions). 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.
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How to Think Like a Computer Scientist: C Version

How to Think Like a Computer Scientist: C Version

The goal of this book, and this class, is to teach you to think like a computer scientist. I like the way computer scientists think because they combine some of the best features of Mathematics, Engineering, and Natural Science. Like math- ematicians, computer scientists use formal languages to denote ideas (specifi- cally 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. By that I mean the ability to formulate problems, think creatively about solu- tions, 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.”
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How to Think Like a Computer Scientist. Java Version

How to Think Like a Computer Scientist. Java Version

The goal of this book, and this class, is to teach you to think like a computer scientist. I like the way computer scientists think because they combine some of the best features of Mathematics, Engineering, and Natural Science. Like math- ematicians, computer scientists use formal languages to denote ideas (specifi- cally 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. By that I mean the ability to formulate problems, think creatively about solu- tions, 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.”
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How to Think Like a Computer Scientist: Learning with Python 3 Documentation - How to Think Like a Computer Scientist - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials

How to Think Like a Computer Scientist: Learning with Python 3 Documentation - How to Think Like a Computer Scientist - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials

Defining the function just tells Python how to do a particular task, not to perform it. In order to execute a function we need to make a function call. We’ve already seen how to call some built-in functions like print, range and int. Function calls contain the name of the function being executed followed by a list of values, called arguments, which are assigned to the parameters in the function definition. So in the second last line of the program, we call the function, and pass alex as the turtle to be manipulated, and 50 as the size of the square we want. While the function is executing, then, the variable size refers to the value 50, and the variable animal refers to the same turtle instance that the variable alex refers to. We called it animal to signify that there is no meaning to the name you give a function argument.
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How to Think Like a Computer Scientist: Learning with Python

How to Think Like a Computer Scientist: Learning with Python

Using a very high-level language like Python allows a teacher to postpone talking about low-level details of the machine until students have the background that they need to better make sense of the details. It thus creates the ability to put “first things first” pedagogically. One of the best examples of this is the way in which Python handles variables. In C++ a variable is a name for a place that holds a thing. Variables have to be declared with types at least in part because the size of the place to which they refer needs to be predetermined. Thus, the idea of a variable is bound up with the hardware of the machine. The powerful and fundamental concept of a variable is already difficult enough for beginning students (in both computer science and algebra). Bytes and addresses do not help the matter. In Python a variable is a name that refers to a thing. This is a far more intuitive concept for beginning students and is much closer to the meaning of “variable” that they learned in their math courses. I had much less difficulty teaching variables this year than I did in the past, and I spent less time helping students with problems using them.
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Python for Software Design   How to Think Like a Computer Scientist pdf

Python for Software Design How to Think Like a Computer Scientist pdf

Programming, especially debugging, sometimes brings out strong emotions. If you are struggling with a difficult bug, you might feel angry, despondent, or embarrassed. There is evidence that people naturally respond to computers as if they were people. †† When they work well, we think of them as teammates, and when they are obstinate or rude, we respond to them the same way we respond to rude, obstinate people. Preparing for these reactions might help you deal with them. One approach is to think of the computer as an employee with certain strengths, like speed and precision, and particular weaknesses, like lack of empathy and inability to grasp the big picture.
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Think Java: How To Think Like a Computer Scientist

Think Java: How To Think Like a Computer Scientist

Computers are often used to automate repetitive tasks. Repeating tasks with- out making errors is something that computers do well and people do poorly. Running the same code multiple times is called iteration. We have seen meth- ods, like countdown and factorial, that use recursion to iterate. Although recursion is elegant and powerful, it takes some getting used to. Java pro- vides language features that make iteration much easier: the while and for statements.

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Think Python: How to Think Like a Computer Scientist

Think Python: How to Think Like a Computer Scientist

Give me a word with three consecutive double letters. I’ll give you a couple of words that almost qualify, but don’t. For example, the word committee, c-o-m-m-i-t-t-e-e. It would be great except for the ‘i’ that sneaks in there. Or Mississippi: M-i-s-s-i-s-s-i- p-p-i. If you could take out those i’s it would work. But there is a word that has three consecutive pairs of letters and to the best of my knowledge this may be the only word. Of course there are probably 500 more but I can only think of one. What is the word? Write a program to find it. Solution: http: // thinkpython. com/ code/ cartalk1. py . Exercise 9.8. Here’s another Car Talk Puzzler (http: // www. cartalk. com/ content/ puzzlers ):
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System Version Document Version C

System Version Document Version C

Although more than one participant can share what’s on their computer screens (like a PowerPoint slide, a spreadsheet, a Web page and so on), you can view only one shared screen at a time. When shared applica- tions are available from multiple participants, the Toggle button turns green, indicating a share is available. You can toggle between multiple shared applications using the Toggle button. Click the button to cycle through the available shares.

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C++ version of the algorithm.

C++ version of the algorithm.

algorithm and our proposed Handel-C version. The superiority of the hardware implementation over the software implementation is clear in both figures. However, for a problem size greater than (64x64), it becomes difficult to measure the execution time of the software (C++) version with the same accuracy of 0.001. At that time, our concern was to force the C++ version of MG to converge at any price. This was only possible by sacrificing with the accuracy of the solution; where we had to gradually increase this factor until we reached an accuracy of 2.0 for a problem size of 2048x2048, in contrast to an accuracy of 0.001 for a problem size of 8x8. On the other hand, Handel- C results were independent from the accuracy of the solution. The accuracy was constant all the way from a problem size of 8x8 to 2048x2048. Obviously, this explains the degeneration of the speedup indicated in Fig. 7.
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How To Program A Computer

How To Program A Computer

Lipari (Scuola Superiore Sant’Anna) OOSD September 23, 2010 4 / 32.. First semester First semester![r]

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DON'T BE SUCH A SCIENTIST

DON'T BE SUCH A SCIENTIST

Which was true. I bore myself sometimes. I learned the art of boredom from my father. He was a military historian, and we were his pupils—my two brothers, two sisters, and I—at the dinner table. He served in Vietnam as a troop advisor in the early 1960s, and he felt a deep need for us all to understand the depth and complexity of the Vietnam problem. But the lectures on Vietnam weren't just about what was going on there at the moment. Oh, no. That would have been too simple and relevant. No, his lectures had to begin at the beginning, back before the American involvement, before the French involvement, back . . . oh, I don't know, maybe in the Paleozoic era or something. He would drone on and on for hours, not telling a story, just ambling about, relaying a stream of consciousness made up of all the disconnected factoids and tidbits floating around in his head. And we were like that “get to the point” audience. (How in the world could I have ever made the same mistake in public? Had to be a genetic element at work.)
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The scientist and the church

The scientist and the church

21st issue of the LRB. We are deeply distressed and dumbfounded at your response, in particular because the LRB piece was a heavily edited (by LRB) version of one chapter (the only chapter on oil) from our just-published book from Verso Afflicted Powers: Capital and Spectacle in a New Age of War in the full version of which we re- peatedly feature, fully credit and highly praise your otherwise unjustly ignored work. The main problem with the LRB piece is that in its extensive and rigorous edit of the original chapter, to fit the journal’s length constraints and house style, LRB excised all our annotations, including the considerable recognition of and citation to your work which appears in our full ‘Blood for Oil?’ chapter. In the section of the book’s chapter (pp. 67-72) which deals directly with your theses, we are explicit that we are rehearsing your work and endorsing the originality and power of your argument, directly citing you six times, and beginning the section with a reference that reads: ‘We are deeply indebted to the brilliant analysis of the political economy of oil of- fered by Jonathan Nitzan and Shimshon Bichler in The Global Political Economy of Israel.’ We begin the following section by saying ‘We take our distance here from Nitzan and Bichler’s analysis,’ once again announcing that what had preceded was a rehearsal of your work, not something we claimed as our own. Finally, in our biblio- graphic Endnote, we say flatly ‘The best political economy of global oil is Jonathan Nitzan and Shimshon Bichler, The Global Political Economy of Israel.’ It is terribly un- fortunate that you had seen none of this when you read the LRB piece.
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One-Year-Olds Think Creatively, Just Like Their Parents

One-Year-Olds Think Creatively, Just Like Their Parents

Creativity is a defining feature of human thinking (Kirton, 1989). It is at the heart of successful human adaptation, both on a large scale (e.g., finding solutions to climate change, or collapsing economies) and small scale (e.g., 3D printers). Divergent thinking (DT) is a measure of creative potential, based on the generation of several ideas within one problem space (Torrance, 1974) . Children’s DT aptitude at 7 years predicts their future creative achievements and careers (Cramond, Matthews-Morgan, Bandalos, & Zuo, 2005; Runco, Millar, Acar, & Cramond, 2010). Thus the capacity to think divergently early in life may be essential for adults to later contribute important, influential ideas to society (Kaufman & Beghetto, 2009). However, given the importance of early DT, it is surprising how little research exists to determine the factors related to its emergence in the first place. The current study will determine whether (1) 1-year- olds can thinking divergently, and (2) toddlers’ DT is linked to parents’ at its emergence. While past research found toddlers can think divergently
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How to Think about Health Promotion Ethics

How to Think about Health Promotion Ethics

Future scholars of health promotion ethics should self-consciously work between social and political philosophy on the one hand and applied, empirically informed, ethics of practice on the other. It is important to be able to map, and debate, competing normative visions of health promotion, including but not limited to the normative ideal we have elaborated here. We should ask how such normative ideals can be defended, but also how norms change in different times and places. We need to attend to principles (such as minimising harm) but also to the contexts that shape policies, norms and practices.
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Reality and Representations: How Americans Think About Agriculture

Reality and Representations: How Americans Think About Agriculture

The advances in social representation theory made by Moscovici and associates are remarkable. However, the style in which they present their arguments is discursive, and the pattern theory nature makes hypothesis testing difficult. Hence, in order to identify hypotheses it is necessary to first isolate the central propositions using more formal conventions. Prior to outlining these formal propositions, I offer a visual map— Figure 3-1— as a way to articulate more explicitly how information flows in social representation theory. This figure is only meant to be illustrative, and is therefore a parsimonious way to show the process involved with one social representation. There are three levels associated with the individual, group, and supra-group, and corresponding to these are attitudes, paradigms, and social representations, respectively. Attitudes refer to the disposition that individuals have towards some object, person, or idea. Paradigms refer to a fundamental model for understanding reality (Babbie 1986; Kuhn 1996[1962]). Social representations are similar to paradigms in terms of being models of reality, but can differ in that they exist across different groups over a period of time.
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How Customers Think Essential Insights into the Mind of the Market

How Customers Think Essential Insights into the Mind of the Market

The Implicit Association Test, or IAT, builds on priming research. It measures how consumers associate certain concepts — for example, "pleasant" or "irritating" — with products or experiences. In one case, a "clicks-and- mortar" company found from the IAT that consumers were more likely to buy some products at a physical store and others on the Internet. The payoff was greater effi- ciency in order processing, fewer returns, lower shipping costs, and higher customer satisfaction.

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Challenging the Computational Metaphor: Implications for How We Think

Challenging the Computational Metaphor: Implications for How We Think

But this observation is not limited to such obviously animate computations as a robot. Consider a video game, a spreadsheet, an automobile’s cruise control system, a cellular telephone network. Like robots, these computations are interactive. What we care about is their ongoing behavior. We do not wait for some hypothetical endpoint to decide whether they have done the right thing, past tense. Instead, expect them to work with us (or with each other, or with our automobile or toaster oven). When we sit down at the computer, we may well have goals. What we expect from a computer is not that it fulfill this goal independently (i.e., compute a "result") but that it cooperate and collaborate with us in our tasks.
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Robots, drugs, reality and education: how the future will change how we think

Robots, drugs, reality and education: how the future will change how we think

Most crucially, then, these changes challenge how we currently understand ourselves to be human. You don’t have to be a believer in the Singularity or transhumanism in order to understand that in the present day we operate with an understanding of the boundaries between our inner lives and the external world, and that technological advances alter how relevant these definitions are. Perhaps the most challenging change of all will be learning to understand that someone in the same space as us may be experiencing a very different reality: just because we are both looking at an object in the same space, there’s no reason any longer to assume that we see the same thing. This will move from being a philosophical and academic question to being a practical issue in our everyday lives. We’ll cope, of course: look at the way we’re evolving expectations around the use of mobile voice technology, with different groups seeing shared norms and rules of behaviour emerge around when it’s polite to let people know you’re taking a call, when it’s better not to, when it’s good to share music with the rest of the bus and when it isn’t. We won’t
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Investing in innovative companies How Private Equity think

Investing in innovative companies How Private Equity think

Enabling process Business model Finance Networking Product performance Offering Product system Service Channel Delivery Brand Customer experience.. Effort is Concentrated in Produc[r]

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