Top PDF Think Java: How To Think Like a Computer Scientist

Think Java: How To Think Like a Computer Scientist

Think Java: How To Think Like a Computer Scientist

a system of equations or finding the roots of a polynomial. It can also be a symbolic computation, like searching and replacing text in a document or (strangely enough) compiling a program. The details look different in different languages, but a few basic instructions appear in just about every language. input: Get data from the keyboard, a file, a sensor, or some other device. output: Display data on the screen, or send data to a file or other device. math: Perform basic mathematical operations like addition and division. decisions: Check for certain conditions and execute the appropriate code. repetition: Perform some action repeatedly, usually with some variation. Believe it or not, that’s pretty much all there is to it. Every program you’ve ever used, no matter how complicated, is made up of small instructions that look much like these. So you can think of programming as the process of breaking down a large, complex task into smaller and smaller subtasks. The process continues until the subtasks are simple enough to be performed with the basic instructions provided by the computer.
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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 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. 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: 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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Python for Software Design   How to Think Like a Computer Scientist pdf

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

Proving that claim is a nontrivial exercise first accomplished by Alan Turing, one of the first computer scientists (some would argue that he was a mathematician, but a lot of early computer scientists started as mathematicians). Accordingly, it is known as the Turing Thesis. For a more complete (and accurate) discussion of the Turing The- sis, I recommend Michael Sipser’s book Introduction to the Theory of Computation. To give you an idea of what you can do with the tools you have learned so far, we’ll evaluate a few recursively defined mathematical functions. A recursive definition is similar to a circular definition, in the sense that the definition contains a reference to the thing being defined. A truly circular definition is not very useful:
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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

• We need to make sure that if we use any data from the web, that we check if the contents are still as we expect them to be. A website may change, or it may disappear. It can also be taken over by a new owner who might change the contents completely. So before you use data from the internet, make your program check if the data is what you want it to be, before executing any code or showing it to any important users! Here is a slightly different example using the requests module. This module is not part of the standard library dis- tributed with python, however it is easier to use and significantly more potent than the urllib module distributed with python. Read requests documentation on http://docs.python-requests.org to learn how to install and use the module. Here, rather than save the web resource to our local disk, we read it directly into a string, and we print that string:
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Think Python: How to Think Like a Computer Scientist

Think Python: How to Think Like a Computer Scientist

This system works fine if the keys are immutable. But if the keys are mutable, like lists, bad things happen. For example, when you create a key-value pair, Python hashes the key and stores it in the corresponding location. If you modify the key and then hash it again, it would go to a different location. In that case you might have two entries for the same key, or you might not be able to find a key. Either way, the dictionary wouldn’t work correctly. That’s why the keys have to be hashable, and why mutable types like lists aren’t. The simplest way to get around this limitation is to use tuples, which we will see in the next chapter.
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How to Think Like a Computer Scientist: Learning with Python

How to Think Like a Computer Scientist: Learning with Python

x Preface seeing this example are looking at their first program. Some of them are undoubt- edly a little nervous, having heard that computer programming is difficult to learn. The C++ version has always forced me to choose between two unsatisfying op- tions: either to explain #include, void main(), {, and }, and risk confusing or intimidating some of the students right at the start, or to tell them, “Just don’t worry about all of that stuff now; we will talk about it later,” and risk the same thing. The educational objectives at this point in the course are to introduce students to the idea of a programming language and to get them to write their first program, thereby introducing them to the programming environment. The Python program has exactly what is needed to do these things, and nothing more. Comparing the explanatory text of the program in each version of the book fur- ther illustrates what this means to the beginning student. There are thirteen paragraphs of explanation of “Hello, world!” in the C++ version; in the Python version, there are only two. More importantly, the missing eleven paragraphs do not deal with the “big ideas” in computer programming but with the minutia of C++ syntax. I found this same thing happening throughout the book. Whole paragraphs simply disappear from the Python version of the text because Python’s much clearer syntax renders them unnecessary.
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At variance with reality: how to re-think our thinking

At variance with reality: how to re-think our thinking

I have a small problem with lists of sustainability oriented competencies, which attempt to lay out what people should learn and acquire to help them cope with emerging conditions and shape a better world. They do have value, and can be helpful. However, they tend to be dauntingly long: I was recently at a workshop in a UK university where lecturers were attempting to grapple with the forty or so competencies suggested by UNECE (2102) as ‘a goal to which all educators should aspire’. More seriously and typically, there is little or no analysis of why such competencies appear to be needed. What is deficient about our current values, understandings, and actions? And, as Raskin asks, why do we think what we do? Without critical reflection at this deeper level, old assumptions and habits - Bateson’s
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Reality and Representations: How Americans Think About Agriculture

Reality and Representations: How Americans Think About Agriculture

The first set of hypotheses is derived from the extension of Propositions 1-3, above, and is summarized in Table 4-1. Note that each specific hypothesis in this table identifies the particular proposition from which it was drawn in the rationale column. In some cases, there is also some existing empirical evidence supporting the hypothesis. The remaining hypotheses in this study—also in Table 4-1—are borrowed directly from past research on attitudes and paradigms. These hypotheses were not originally formulated with social representation theory in mind, but a connection can be forged, as gender, age, race, education, income, socioeconomic status, and region of the country all play a role in defining the types of groups to which people belong. Since group membership is central to social representation theory, these variables should shape exposure, acceptance, and use of social representations (Breakwell 1993). I will now elaborate on how these particular characteristics should be related to agricultural thought.
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Meaning and uselessness: how to think about derogatory words

Meaning and uselessness: how to think about derogatory words

There is one very large question to which I hope to make a very small contribution here—whether so-called representationalism in semantics serves philosophers’ purposes, or whether some other approach is needed. Derogatory words might seem to require something different. But I shall find fault with the treatment of these words given in such other approaches as I consider, and I shall make a suggestion about how a representationalist can think about them. Some of the interest of the argument lies in diagnosing the difficulties with a noncognitivist and a certain sort of expressivist treatment of derogatory words: the diagnoses direct us to treat words as components of social practices that can change.
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A Place to Think

A Place to Think

It was the month of May. In a large conference room, more than 800 educators were gathered: teachers, consultants, in-school and board- level administrators. A number of us had come here reluctantly to attend an imposed three-day session on what we feared might be another proposed miracle cure for the problems of education. A panel of speakers stood on stage. I could feel my own scepticism and tried to tame it. The first speaker launched into his initial words. He began by showing us pictures of his family, recounting with humour the challenges of being married to a teacher and the hopes and aspirations he had for his children. With a mix of self-derision and a measure of pride, he spoke of the meanders of his own life. The mood shifted in the room, from a “here we are at a conference” to a “here we are”; I sensed it in myself and in the people around my table. The woman sitting next to me whispered “I really like this guy! He is real.” While this was a very public setting, he was speaking to each of us from within, and, as a result, I was – we were, it seemed – ready to listen and to hear from within. Dobson (2015) states that “Although who is invisible to the eye, who is nonetheless identifiable by a reason of a felt radiance”(p. 194). I felt that radiance, the real possibility of a who- to-who connection. Would I have been able to identify this before my journey of heuristic inquiry? (Saada, 2018, p. 194)
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One-Year-Olds Think Creatively, Just Like Their Parents

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

This study shows, for the first time, that DT processes may exist, and appear to be measurable, in the second year. It thus provides the earliest window to date to examine how DT emerges. This study converges with evidence that young children are good explorers in general (Bonawitz et al., 2011; van Schijndel, Franse, & Raijmakers, 2010; van Schijndel, Singer, van der Maas, & Raijmakers, 2010). Additionally, by demonstrating that DT is measurable early on, this opens up the possibility to determine the initial factors which affect DT at its onset. For instance, we could examine whether executive function affects DT in toddlers, as it does in adults (Zabelina & Robinson, 2010).
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MoL 2015 14: 
  How Difficult is it to Think that you Think that I Think that   ? A DEL based Computational level Model of Theory of Mind and its Complexity

MoL 2015 14: How Difficult is it to Think that you Think that I Think that ? A DEL based Computational level Model of Theory of Mind and its Complexity

In a less recent debate in the philosophy of mind there is the question regarding the realism of mental states and consequently whether mental states can be investigated scientifically. On the one hand, there are realists like Jerry Fodor (1987), who claim that the success of everyday explanations of behavior in terms of mental states, also called “folk psychology,” indicates the existence of mental states. On the other hand, there are eliminativists like Paul Churchland (1981), who claim that folk psychology is a false theory and that the mental states that it involves are not real. Referring to mental states for psychological explanation is non-scientific and should not be incorporated into scientific theories. Finally, there are the moderate realists, or instrumentalists, like Daniel Dennett (1987), who agree that common-sense psychology is highly successful, but deny that this implies the independent existence of the mental states involved. Mental state attributions are only true and real in so far as they help us to successfully explain behavior that cannot be explained otherwise (Pitt, 2013). We believe that the fact that we (seem to) use ToM successfully (at least in some cases) is enough justification for scientific investigation, regardless of the (independent) existence of mental states.
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Challenging the Computational Metaphor: Implications for How We Think

Challenging the Computational Metaphor: Implications for How We Think

The traditional computational metaphor is also problematic as a guiding epistemology. In our classrooms, certain styles of thinking and understanding are discouraged for deviating from the unrelenting sequentialism of the computational metaphor. Turkle (1984; Turkle and Papert 1990) studied how programming is presented as a rigidly linear, sequential, and logical process. For some students—those she identifies as bricoleurs or tinkerers—this way of decomposing problems is uncomfortable. These students prefer to experiment with partial programs, piecing them together to build larger structures only as they become comfortable with how they interact. Frustrated by black-boxing and modular-functional linear design, many of Turkle's tinkerers abandoned computer science. Those who did remain succeeded by suppressing, or at least hiding, their epistemological style. Turkle notes that this style is disproportionately observed among female students, giving rise to one possible explanation of the differential representation of women within the field. Further, componential tinkering may be precisely what is needed in today’s toolkit- and library-rich programming environment.
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At variance with reality: how to re-think our thinking

At variance with reality: how to re-think our thinking

Integrative thinking responds to the challenges of sustainable development that are simultaneously global and local and require an awareness of how change in one part of the world can impact upon other parts, as well as an awareness of how choices today can impact tomorrow’s world. These challenges are complex and require inputs from a range of disciplines to address them, including perspectives on natural, social and economic sys- tems. Different cultures and world-views can provide valuable insights; at its most funda- mental, sustainable development connects individuals and groups to other people, locally and globally, and to their natural environment. Integrative thinking implies ways of thinking and acting that reflect these interrelationships and the creative possibilities that they engender. Systems thinking is a valuable tool in achieving such an integrative approach. Inclusivity refers to a willingness to incorporate a range of perspectives critical to negotia- ting a sustainable future. Sustainable development issues are often characterized by con- tradictions and dilemmas; different perspectives can both underpin and provide solutions to these issues. While embracing different perspectives, it is important for educators to be open about their own world-views so that these are not hidden from learners nor imposed upon them.
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To Think or Not to Think?: A New Perspective on Optimal Consumer Decision Making

To Think or Not to Think?: A New Perspective on Optimal Consumer Decision Making

The Powerful Unconscious view offers an alternative approach to how consumers should think before making these major decisions. Unconscious thought is suggested to have greater information processing capacity and consumers are suggested to be more objective during information processing in these settings (Dijksterhuis 2004; Dijksterhuis and Nordgren 2006; Wilson 2002). This increased capacity allows individuals to more extensively consider a set of information. Furthermore, the unconscious is suggested to more objectively weigh product attributes and avoid influence from secondary factors that are not necessarily representative of the best choice. As a result, choice should be based primarily on a comprehensive consideration of the most important attributes to the decision. However, empirical findings have failed to support these explanations of why unconscious thought might be optimal. Unconscious thought does not appear to increase attribute knowledge (thus ruling out capacity explanations) or improve the decision maker’s ability to weigh which information is important (e.g. Gonzalez-Vallejo et al. 2008; Newell et al. 2009). Together, these recent findings suggest that if unconscious thought does indeed optimize choice quality when making major purchase decisions, a new theoretical explanation is needed to explain this effect.
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What I think when I think about treebanks

What I think when I think about treebanks

In addition to sampling data adversarially, introducing multiple splits, and collecting multiple, unadju- dicated annotations, I also would like to question another straight-jacket in treebanking projects, namely the need for our annotations to be well-formed trees (or directed acyclic graphs for that matter). Some linguists have argued that some sentences are best described by cyclic structures, for example (Pollard and Sag, 1994). Such analyses never make it into treebanks,10 and I think the main motivation is the idea that modern parsers require well-formed input trees.

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Think Global, Think Local: Critical regionalism and Landscape Architecture

Think Global, Think Local: Critical regionalism and Landscape Architecture

Although landscape is increasingly recognised within the critical regionalist discourse, one of the challenges for pursuing a critically regionalist response in landsc[r]

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If You Think 9 Ending Prices Are Low, Think Again

If You Think 9 Ending Prices Are Low, Think Again

Cross-Correlograms of the Percentage Differences between Average 9-Ending and Non 9Ending Prices, Regular and Sale Prices, on a Weekly Basis, by Product Categories at the Product-Store L[r]

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