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e-book
Pharo is a clean, innovative, open-source, live-programming environment. Deep into Pharois the second volume of a series of books covering Pharo. Whereas the first volume is intended for newcomers, this second volume covers deeper topics.You will learn about Pharo frameworks and libraries such as Glamour, PetitParser, Roassal, FileSystem, Regex, and Socket. You will explore the language with chapters on exceptions, blocks, small integers, and floats. You will discover tools such as profilers, Metacello and Gofer.
- Subjects:
- Computing
- Keywords:
- Textbooks Smalltalk-80 (Computer program language)
- Resource Type:
- e-book
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e-book
Pharo is an open-source, elegant and pure object-oriented language that supports truly immersive and life programming experience. Pharo offers excellent tools such as hot-debuggers and on the fly code update that change the programming experience. More at http://www.pharo.org.Pharo is a powerful language and IDE that companies use to deliver complex business-effective applications. More at: http://www.pharo.org/success In Pharo everything is an object, and anything can change at run-time under your fingers. Pharo is written in itself you can explore a complete world. You can feel and talk to objects. But Pharo does not stop there, with Pharo you can improve your object-oriented skills by rediscovering the essence of object-oriented programming. Pharo by Example 50, intended for both students and developers, will guide you gently through the Pharo language and environment by means of a series of examples and exercises. This book is available under the Creative Commons Attribution-ShareAlike 3.0 license.
- Subjects:
- Computing
- Keywords:
- Textbooks Smalltalk-80 (Computer program language)
- Resource Type:
- e-book
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e-book
Squeak is a modern open-source development environment for the classic Smalltalk-80 programming language. Despite being the first purely object-oriented language and environment, Smalltalk is in many ways still far ahead of its successors in promoting a vision of an environment where everything is an object, and anything can change at run-time. Squeak by Example, intended for both students and developers, will guide you gently through the Squeak language and environment by means of a series of examples and exercises. The book helps you get started with A Quick Tour of Squeak and guides you through A First Application. The Smalltalk language is introduced in three chapters on Syntax in a Nutshell, Understanding Message Syntax and The Smalltalk Object Model. Development with Squeak is covered in The Squeak Programming Environment and SUnit. Several of the key classes are presented in chapters on Basic Classes, Collections, Streams and Morphic. The first edition of the book concludes with chapters on Classes and Metaclasses and Frequently Asked Questions.
- Subjects:
- Computing
- Keywords:
- Multimedia systems Squeak Textbooks Smalltalk-80 (Computer program language)
- Resource Type:
- e-book
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e-book
Think DSP is an introduction to Digital Signal Processing in Python. The premise of this book (and the other books in the Think X series) is that if you know how to program, you can use that skill to learn other things. The author is writing this book because he thinks the conventional approach to digital signal processing is backward: most books (and the classes that use them) present the material bottom-up, starting with mathematical abstractions like phasors.
- Subjects:
- Electrical Engineering and Computing
- Keywords:
- Signal processing -- Digital techniques -- Data processing Python (Computer program language) Textbooks
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- e-book
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e-book
This book is about complexity science, data structures and algorithms, intermediate programming in Python, and the philosophy of science: Data structures and algorithms: A data structure is a collection that contains data elements organized in a way that supports particular operations. For example, a dictionary organizes key-value pairs in a way that provides fast mapping from keys to values, but mapping from values to keys is generally slower. An algorithm is a mechanical process for performing a computation. Designing efficient programs often involves the co-evolution of data structures and the algorithms that use them. For example, the first few chapters are about graphs, a data structure that is a good implementation of a graph---nested dictionaries---and several graph algorithms that use this data structure. Python programming: This book picks up where Think Python leaves off. I assume that you have read that book or have equivalent knowledge of Python. As always, I will try to emphasize fundmental ideas that apply to programming in many languages, but along the way you will learn some useful features that are specific to Python. Computational modeling: A model is a simplified description of a system that is useful for simulation or analysis. Computational models are designed to take advantage of cheap, fast computation. Philosophy of science: The models and results in this book raise a number of questions relevant to the philosophy of science, including the nature of scientific laws, theory choice, realism and instrumentalism, holism and reductionism, and Bayesian epistemology. This book focuses on discrete models, which include graphs, cellular automata, and agent-based models. They are often characterized by structure, rules and transitions rather than by equations. They tend to be more abstract than continuous models; in some cases there is no direct correspondence between the model and a physical system. Complexity science is an interdisciplinary field---at the intersection of mathematics, computer science and physics---that focuses on these kinds of models. That's what this book is about.
- Subjects:
- Computing
- Keywords:
- Computational complexity Python (Computer program language) Textbooks
- Resource Type:
- e-book
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e-book
Think Bayes is an introduction to Bayesian statistics using computational methods. The premise of this book, and the other books in the Think X series, is that if you know how to program, you can use that skill to learn other topics. Most books on Bayesian statistics use mathematical notation and present ideas in terms of mathematical concepts like calculus. This book uses Python code instead of math, and discrete approximations instead of continuous mathematics. As a result, what would be an integral in a math book becomes a summation, and most operations on probability distributions are simple loops. I think this presentation is easier to understand, at least for people with programming skills. It is also more general, because when we make modeling decisions, we can choose the most appropriate model without worrying too much about whether the model lends itself to conventional analysis. Also, it provides a smooth development path from simple examples to real-world problems.
- Subjects:
- Computing and Mathematics and Statistics
- Keywords:
- Bayesian statistical decision theory Python (Computer program language) Textbooks
- Resource Type:
- e-book
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e-book
Think Stats is an introduction to Probability and Statistics for Python programmers. Think Stats emphasizes simple techniques you can use to explore real data sets and answer interesting questions. The book presents a case study using data from the National Institutes of Health. Readers are encouraged to work on a project with real datasets. If you have basic skills in Python, you can use them to learn concepts in probability and statistics. Think Stats is based on a Python library for probability distributions (PMFs and CDFs). Many of the exercises use short programs to run experiments and help readers develop understanding.
- Subjects:
- Computing and Mathematics and Statistics
- Keywords:
- Textbooks Statistics -- Computer programs
- Resource Type:
- e-book
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e-book
Think Java is a hands-on introduction to computer science and programming used by many universities and high schools around the world. Its conciseness, emphasis on vocabulary, and informal tone make it particularly appealing for readers with little or no experience. The book starts with the most basic programming concepts and gradually works its way to advanced object-oriented techniques. In this fully updated and expanded edition, authors Allen Downey and Chris Mayfield introduce programming as a means for solving interesting problems. Each chapter presents material for one week of a college course and includes exercises to help you practice what you’ve learned. Along the way, you’ll see nearly every topic required for the AP Computer Science A exam and Java SE Programmer I certification.
- Subjects:
- Computing
- Keywords:
- Java (Computer program language) Computer programming Programming languages (Electronic computers) Textbooks
- Resource Type:
- e-book
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e-book
This book focuses on the discrete Fourier transform (DFT), discrete convolution, and, particularly, the fast algorithms to calculate them. These topics have been at the center of digital signal processing since its beginning, and new results in hardware, theory and applications continue to keep them important and exciting. This book uses an index map, a polynomial decomposition, an operator factorization, and a conversion to a filter to develop a very general and efficient description of fast algorithms to calculate the discrete Fourier transform (DFT). The work of Winograd is outlined, chapters by Selesnick, Pueschel, and Johnson are included, and computer programs are provided.
- Subjects:
- Computing and Mathematics and Statistics
- Keywords:
- Fourier transformations Textbooks
- Resource Type:
- e-book
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e-book
Introduction to the Modeling and Analysis of Complex Systems introduces students to mathematical/computational modeling and analysis developed in the emerging interdisciplinary field of Complex Systems Science. Complex systems are systems made of a large number of microscopic components interacting with each other in nontrivial ways. Many real-world systems can be understood as complex systems, where critically important information resides in the relationships between the parts and not necessarily within the parts themselves. This textbook offers an accessible yet technically-oriented introduction to the modeling and analysis of complex systems. The topics covered include: fundamentals of modeling, basics of dynamical systems, discrete-time models, continuous-time models, bifurcations, chaos, cellular automata, continuous field models, static networks, dynamic networks, and agent-based models. Most of these topics are discussed in two chapters, one focusing on computational modeling and the other on mathematical analysis. This unique approach provides a comprehensive view of related concepts and techniques, and allows readers and instructors to flexibly choose relevant materials based on their objectives and needs. Python sample codes are provided for each modeling example.
- Subjects:
- Computing
- Keywords:
- System analysis -- Mathematical models Computational complexity Textbooks System theory -- Mathematical models
- Resource Type:
- e-book