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This is a first draft of a free (as in speech, not as in beer, [Sta02]) (although it is free as in beer as well) textbook for a one-semester, undergraduate statistics course. It was used for Math 156 at Colorado State University–Pueblo in the spring semester of 2017.
- Subjects:
- Mathematics and Statistics
- Keywords:
- Textbooks Statistics
- Resource Type:
- e-book
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e-book
Delftse Foundations of Computation is a textbook for a one quarter introductory course in theoretical computer science. It includes topics from propositional and predicate logic, proof techniques, set theory and the theory of computation, along with practical applications to computer science. It has no prerequisites other than a general familiarity with computer programming.
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Textbooks Computer science
- Resource Type:
- e-book
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e-book
Business Mathematics was written to meet the needs of a twenty-first century student. It takes a systematic approach to helping students learn how to think and centers on a structured process termed the PUPP Model (Plan, Understand, Perform, and Present). This process is found throughout the text and in every guided example to help students develop a step-by-step problem-solving approach. This textbook simplifies and integrates annuity types and variable calculations, utilizes relevant algebraic symbols, and is integrated with the Texas Instruments BAII+ calculator. It also contains structured exercises, annotated and detailed formulas, and relevant personal and professional applications in discussion, guided examples, case studies, and even homework questions.
- Subjects:
- Mathematics and Statistics
- Keywords:
- Textbooks Business mathematics
- Resource Type:
- e-book
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e-book
This text is a practical guide for linguists, and programmers, who work with data in multilingual computational environments. We introduce the basic concepts needed to understand how writing systems and character encodings function, and how they work together at the intersection between the Unicode Standard and the International Phonetic Alphabet. Although these standards are often met with frustration by users, they nevertheless provide language researchers and programmers with a consistent computational architecture needed to process, publish and analyze lexical data from the world's languages. Thus we bring to light common, but not always transparent, pitfalls which researchers face when working with Unicode and IPA. Having identified and overcome these pitfalls involved in making writing systems and character encodings syntactically and semantically interoperable (to the extent that they can be), we created a suite of open-source Python and R tools to work with languages using orthography profiles that describe author- or document-specific orthographic conventions. In this cookbook we describe a formal specification of orthography profiles and provide recipes using open source tools to show how users can segment text, analyze it, identify errors, and to transform it into different written forms for comparative linguistics research.
- Subjects:
- Computing, Data Science and Artificial Intelligence and Language and Languages
- Keywords:
- Textbooks Unicode (Computer character set) Language languages -- Orthography spelling
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- e-book
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e-book
Data structures and algorithms are among the most important inventions of the last 50 years, and they are fundamental tools software engineers need to know. But in my opinion, most of the books on these topics are too theoretical, too big, and too bottom-up: Too theoretical: Mathematical analysis of algorithms is based on simplifying assumptions that limit its usefulness in practice. Many presentations of this topic gloss over the simplifications and focus on the math. In this book I present the most practical subset of this material and eliminate the rest. Too big: Most books on these topics are at least 500 pages, and some are more than 1000. By focusing on the topics I think are most useful for software engineers, I kept this book under 250 pages. Too bottom-up: Many data structures books focus on how data structures work (the implementations), with less about how to use them (the interfaces). In this book, I go “top down”, starting with the interfaces. Readers learn to use the structures in the Java Collections Framework before getting into the details of how they work. Finally, many present this material out of context and without motivation: it’s just one damn data structure after another! I try to alleviate the boredom by organizing the topics around an application—web search—that uses data structures extensively, and is an interesting and important topic in its own right. This application also motivates some topics that are not usually covered in an introductory data structures class, including persistent data structures, with Redis, and streaming algorithms. This book also presents basic aspects of software engineering practice, including version control and unit testing. Each chapter ends with an exercise that allows readers to apply what they have learned. Each exercise includes automated tests that check the solution. And for most exercises, I present my solution at the beginning of the next chapter. This book is intended for college students in computer science and related fields, as well as professional software engineers, people training in software engineering, and people preparing for technical interviews. I assume that the reader knows Java at an intermediate level, but I explain some Java features along the way, and provide pointers to supplementary material. People who have read Think Java or Head First Java are prepared for this book.
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Java (Computer program language) Textbooks Data structures (Computer science)
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- e-book
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e-book
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 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 trade offs 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 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.”
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Programming languages (Electronic computers) Computer programming Textbooks C (Computer program language)
- Resource Type:
- e-book
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e-book
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 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 trade offs 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 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.”
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e-book
The documentation is missing or obsolete, and the original developers have departed. Your team has limited understanding of the system, and unit tests are missing for many, if not all, of the components. When you fix a bug in one place, another bug pops up somewhere else in the system. Long rebuild times make any change difficult. All of these are signs of software that is close to the breaking point. Many systems can be upgraded or simply thrown away if they no longer serve their purpose. Legacy software, however, is crucial for operations and needs to be continually available and upgraded. How can you reduce the complexity of a legacy system sufficiently so that it can continue to be used and adapted at acceptable cost? Based on the authors' industrial experiences, this book is a guide on how to reverse engineer legacy systems to understand their problems, and then reengineer those systems to meet new demands. Patterns are used to clarify and explain the process of understanding large code bases, hence transforming them to meet new requirements. The key insight is that the right design and organization of your system is not something that can be evident from the initial requirements alone, but rather as a consequence of understanding how these requirements evolve.
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Software patterns Object-oriented programming (Computer science) Textbooks Software reengineering
- Resource Type:
- e-book
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e-book
The precursors to what we study today as Trigonometry had their origin in ancient Mesopotamia, Greece and India. These cultures used the concepts of angles and lengths as an aid to understanding the movements of the heavenly bodies in the night sky. Ancient trigonometry typically used angles and triangles that were embedded in circles so that many of the calculations used were based on the lengths of chords within a circle. The relationships between the lengths of the chords and other lines drawn within a circle and the measure of the corresponding central angle represent the foundation of trigonometry - the relationship between angles and distances.
- Subjects:
- Mathematics and Statistics
- Keywords:
- Trigonometry Precalculus Textbooks
- Resource Type:
- e-book
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e-book
This College Algebra text will cover a combination of classical algebra and analytic geometry, with an introduction to the transcendental exponential and logarithmic functions. If mathematics is the language of science, then algebra is the grammar of that language. Like grammar, algebra provides a structure to mathematical notation, in addition to its uses in problem solving and its ability to change the appearance of an expression without changing the value.
- Subjects:
- Mathematics and Statistics
- Keywords:
- Trigonometry Algebra Textbooks
- Resource Type:
- e-book