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Introduction to Discrete Mathematics with ISETL
Intended for first- or second-year undergraduates, this introduction to discrete mathematics covers the usual topics of such a course, but applies constructivist principles that promote - indeed, require - active participation by the student. Working with the programming language ISETL, whose syntax is close to that of standard mathematical language, the student constructs the concepts in her or his mind as a result of constructing them on the computer in the syntax of ISETL. This dramatically different approach allows students to attempt to discover concepts in a "Socratic" dialog with the computer. The discussion avoids the formal "definition-theorem" approach and promotes active involvement by the reader by its questioning style. An instructor using this text can expect a lively class whose students develop a deep conceptual understanding rather than simply manipulative skills. Topics covered in this book include: the propositional calculus, operations on sets, basic counting methods, predicate calculus, relations, graphs, functions, and mathematical induction.
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Programming-Based Formal Languages and Automata Theory
This textbook introductes formal languages and automata theory for upper-level undergraduate or beginning graduate students. While it contains the traditional mathematical development usually employed in computational theory courses, it is also quite different from many of them. Machines, grammars, and algorithms developed as part of a constructive proof are intended to be rendered as programs. The book is divided into four parts that build on each other. Part I reviews fundamental concepts. It introduces programming in FSM and reviews program design. In addition, it reviews essential mathematical background on sets, relations, and reasoning about infinite sets. Part II starts the study of formal languages and automata theory in earnest with regular languages. It first introduces regular expressions and shows how they are used to write programs that generate words in a regular language. Given that regular expressions generate words, it is only natural to ask how a machine can recognize words in a regular language. This leads to the study of deterministic and nondeterministic finite-state machines. Part III starts the exploration of languages that are not regular with context-free languages. It begins with context-free grammars and pushdown automata to generate and recognize context-free languages, and it ends with a discussion of deterministic pushdown automata and illustrates why these automatons are fundamentally different from nondeterministic pushdown automata. Part IV eventually explores languages that are not context-free, known as context-sensitive languages. It starts by discussing the most powerful automaton known to mankind: the Turing machine. It then moves to grammars for context-sensitive languages, and their equivalence with Turing machines is explored. The book ends with a brief chapter introducing complexity theory and explores the question of determining if a solution to a problem is practical.
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Digital Signal Processing (DSP) with Python Programming
The parameter estimation and hypothesis testing are the basic tools in statistical inference. These techniques occur in many applications of data processing., and methods of Monte Carlo have become an essential tool to assess performance. For pedagogical purposes the book includes several computational problems and exercices. To prevent students from getting stuck on exercises, detailed corrections are provided.
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Python for Signal Processing
This book covers the fundamental concepts in signal processing illustrated with Python code and made available via IPython Notebooks, which are live, interactive, browser-based documents that allow one to change parameters, redraw plots, and tinker with the ideas presented in the text. Everything in the text is computable in this format and thereby invites readers to “experiment and learn” as they read. The book focuses on the core, fundamental principles of signal processing. The code corresponding to this book uses the core functionality of the scientific Python toolchain that should remain unchanged into the foreseeable future. For those looking to migrate their signal processing codes to Python, this book illustrates the key signal and plotting modules that can ease this transition. For those already comfortable with the scientific Python toolchain, this book illustrates the fundamental concepts in signal processing and provides a gateway to further signal processing concepts.
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Python For ArcGIS
This book introduces Python scripting for geographic information science (GIS) workflow optimization using ArcGIS. It builds essential programming skills for automating GIS analysis. Over 200 sample Python scripts and 175 classroom-tested exercises reinforce the learning objectives. Readers will learn to: • Write and run Python in the ArcGIS Python Window, the PythonWin IDE, and the PyScripter IDE • Work with Python syntax and data types • Call ArcToolbox tools, batch process GIS datasets, and manipulate map documents using the arcpy package • Read and modify proprietary and ASCII text GIS data • Parse HTML web pages and KML datasets • Create Web pages and fetch GIS data from Web sources. • Build user-interfaces with the native Python file dialog toolkit or the ArcGIS Script tools and PyToolboxes Python for ArcGIS is designed as a primary textbook for advanced-level students in GIS. Researchers, government specialists and professionals working in GIS will also find this book useful as a reference.
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Python GUI Programming Cookbook
Over 80 object-oriented recipes to help you create mind-blowing GUIs in PythonAbout This Book• Use object-oriented programming to develop amazing GUIs in Python• Create a working GUI project as a central resource for developing your Python GUIs• Packed with easy-to-follow recipes to help you develop code using the latest released version of PythonWho This Book Is ForIf you are a Python programmer with intermediate level knowledge of GUI programming and want to learn how to create beautiful, effective, and responsive GUIs using the freely available Python GUI frameworks, this book is for you.What You Will Learn• Create amazing GUIs with Python's built-in Tkinter module• Customize the GUIs by using layout managers to arrange the GUI widgets• Advance to an object-oriented programming style using Python• Develop beautiful charts using the free Matplotlib Python module• Use threading in a networked environment to make the GUIs responsive• Discover ways to connect the GUIs to a database• Understand how unit tests can be created and internationalize the GUI• Extend the GUIs with free Python frameworks using best practices In DetailPython is a multi-domain, interpreted programming language. It is a widely used general-purpose, high-level programming language. It is often used as a scripting language because of its forgiving syntax and compatibility with a wide variety of different eco-systems. Its flexible syntax enables developers to write short scripts while at the same time, they can use object-oriented concepts to develop very large projects.Python GUI Programming Cookbook follows a task-based approach to help you create beautiful and very effective GUIs with the least amount of code necessary. This book uses the simplest programming style, using the fewest lines of code to create a GUI in Python, and then advances to using object-oriented programming in later chapters. If you are new to object-oriented programming (OOP), this book will teach you how to take advantage of the OOP coding style in the context of creating GUIs written in Python.Throughout the book, you will develop an entire GUI application, building recipe upon recipe, connecting the GUI to a database. In the later chapters, you will explore additional Python GUI frameworks, using best practices. You will also learn how to use threading to ensure your GUI doesn't go unresponsive.By the end of the book, you will be an expert in Python GUI programming to develop a common set of GUI applications.Style and approachEvery recipe in this programming cookbook solves a problem you might encounter in your programming career. At the same time, most of the recipes build on each other to create an entire, real-life GUI application.
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Pearson Mathematics for the Middle Years Programme Year 4+5 Standard
This brand new series puts learners in charge with an exploratory inquiry-led approach to MYP Mathematics. Each full-colour book and accompanying eBook contains detailed worked examples, reflections, differentiated exercises, and check your knowledge questions to put learning into practice. Clear links to key concepts, related concepts and global contexts in addition to statements of inquiry and inquiry questions for each chapter. ATLs identified throughout. Investigations encourage learners to seek knowledge and develop ATL skills. Written by an international team of highly experienced authors and teachers, and led by Series Editor, Ibrahim Wazir, this new series matches the 2020 Subject Guide.
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Mathematics for Computer Scientists
This textbook contains the mathematics needed to study computer science in application-oriented computer science courses. The content is based on the author's many years of teaching experience.The translation of the original German 7th edition Mathematik für Informatiker by Peter Hartmann was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content.Textbook FeaturesYou will always find applications to computer science in this book.Not only will you learn mathematical methods, you will gain insights into the ways of mathematical thinking to form a foundation for understanding computer science.Proofs are given when they help you learn something, not for the sake of proving.Mathematics is initially a necessary evil for many students. The author explains in each lesson how students can apply what they have learned by giving many real world examples, and by constantly cross-referencing math and computer science. Students will see how math is not only useful, but can be interesting and sometimes fun.The ContentSets, logic, number theory, algebraic structures, cryptography, vector spaces, matrices, linear equations and mappings, eigenvalues, graph theory.Sequences and series, continuous functions, differential and integral calculus, differential equations, numerics.Probability theory and statistics.The Target AudiencesStudents in all computer science-related coursework, and independent learners.
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Advanced Python Programming
Write fast, robust, and highly reusable applications using Python's internal optimization, state-of-the-art performance-benchmarking tools, and cutting-edge librariesKey FeaturesBenchmark, profile, and accelerate Python programs using optimization toolsScale applications to multiple processors with concurrent programmingMake applications robust and reusable using effective design patternsBook DescriptionPython's powerful capabilities for implementing robust and efficient programs make it one of the most sought-after programming languages.In this book, you'll explore the tools that allow you to improve performance and take your Python programs to the next level.This book starts by examining the built-in as well as external libraries that streamline tasks in the development cycle, such as benchmarking, profiling, and optimizing. You'll then get to grips with using specialized tools such as dedicated libraries and compilers to increase your performance at number-crunching tasks, including training machine learning models.The book covers concurrency, a major solution to making programs more efficient and scalable, and various concurrent programming techniques such as multithreading, multiprocessing, and asynchronous programming.You'll also understand the common problems that cause undesirable behavior in concurrent programs.Finally, you'll work with a wide range of design patterns, including creational, structural, and behavioral patterns that enable you to tackle complex design and architecture challenges, making your programs more robust and maintainable.By the end of the book, you'll be exposed to a wide range of advanced functionalities in Python and be equipped with the practical knowledge needed to apply them to your use cases.What you will learnWrite efficient numerical code with NumPy, pandas, and XarrayUse Cython and Numba to achieve native performanceFind bottlenecks in your Python code using profilersOptimize your machine learning models with JAXImplement multithreaded, multiprocessing, and asynchronous programsSolve common problems in concurrent programming, such as deadlocksTackle architecture challenges with design patternsWho this book is forThis book is for intermediate to experienced Python programmers who are looking to scale up their applications in a systematic and robust manner. Programmers from a range of backgrounds will find this book useful, including software engineers, scientific programmers, and software architects.
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Oxford Mathematics Primary Years Programme Teacher Book 1
Providing comprehensive coverage of the PYP Mathematics Scope and Sequence, these Teacher Books provide a wealth of additional teacher support to accompany the Oxford Mathematics Primary Years Programme Student and Practice and Mastery Books.· Cover the five strands of Number, Pattern and Function, Measurement, Shape and Space, and Data Handling using the PYP methodology of constructing, transferring and applying meaning · Measure progress using pre- and post-assessments· Plan individual, group and class activities thanks to extensive teaching support, including planning suggestions, worksheets and answers· Support and extend learning via reinforcement activities
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Python Automation For Dummies
Streamline Your Workflow and Boost Productivity with Python Automation In today's workplaces, there's a high demand for know-how on the Python programming language, especially for writing time-saving scripts that can simplify routine work tasks. Python Automation For Dummies delivers, with simple explanations of how you can use Python to automatically wrangle data files, manage media files, create shortcuts, find and organize web data, and even analyze social media for trends. With this easy-to-follow Dummies guide, you can upskill, expand your productivity, and speed up the process of generating data-driven insights. You'll even learn to enhance your Python automations with AI, for workflows that are faster and smarter. Review the basics of Python coding and follow steps for automating all sorts of tasksManage large file sets, organize and analyze data, and speed up research processesAutomate scheduling and other time-consuming tasks—and optimize work with AIFree up time and resources by automating routine work, so you can foucs on more important issues This is a great Dummies resource for Python developers interested in applying the popular coding language to make workflows more efficient.
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Mathematical Programming and Financial Objectives for Scheduling Projects
Mathematical Programming and Financial Objectives for Scheduling Projects focuses on decision problems where the performance is measured in terms of money. As the title suggests, special attention is paid to financial objectives and the relationship of financial objectives to project schedules and scheduling. In addition, how schedules relate to other decisions is treated in detail. The book demonstrates that scheduling must be combined with project selection and financing, and that scheduling helps to give an answer to the planning issue of the amount of resources required for a project. The author makes clear the relevance of scheduling to cutting budget costs. The book is divided into six parts. The first part gives a brief introduction to project management. Part two examines scheduling projects in order to maximize their net present value. Part three considers capital rationing. Many decisions on selecting or rejecting a project cannot be made in isolation and multiple projects must be taken fully into account. Since the requests for capital resources depend on the schedules of the projects, scheduling taken on more complexity. Part four studies the resource usage of a project in greater detail. Part five discusses cases where the processing time of an activity is a decision to be made. Part six summarizes the main results that have been accomplished.
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Oxford Mathematics Primary Years Programme Student Book 4
Build mathematical knowledge and skills and explore the PYP transdisciplinary themes via this colourful, inquiry-based Student Book.· Fully support the PYP approach with comprehensive coverage of the PYP Mathematics Scope and Sequence· Progressively build understanding via guided, independent and extended learning activities· Cover the five strands of Number, Pattern and Function, Measurement, Shape and Space, and Data Handling using the PYP methodology of constructing, transferring and applying meaning· Encourage learners to explore and apply knowledge using real-world problems
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Mastering Python for Finance
Take your financial skills to the next level by mastering cutting-edge mathematical and statistical financial applicationsKey FeaturesExplore advanced financial models used by the industry and ways of solving them using PythonBuild state-of-the-art infrastructure for modeling, visualization, trading, and moreEmpower your financial applications by applying machine learning and deep learningBook DescriptionThe second edition of Mastering Python for Finance will guide you through carrying out complex financial calculations practiced in the industry of finance by using next-generation methodologies. You will master the Python ecosystem by leveraging publicly available tools to successfully perform research studies and modeling, and learn to manage risks with the help of advanced examples.You will start by setting up your Jupyter notebook to implement the tasks throughout the book. You will learn to make efficient and powerful data-driven financial decisions using popular libraries such as TensorFlow, Keras, Numpy, SciPy, and sklearn. You will also learn how to build financial applications by mastering concepts such as stocks, options, interest rates and their derivatives, and risk analytics using computational methods. With these foundations, you will learn to apply statistical analysis to time series data, and understand how time series data is useful for implementing an event-driven backtesting system and for working with high-frequency data in building an algorithmic trading platform. Finally, you will explore machine learning and deep learning techniques that are applied in finance.By the end of this book, you will be able to apply Python to different paradigms in the financial industry and perform efficient data analysis.What you will learnSolve linear and nonlinear models representing various financial problemsPerform principal component analysis on the DOW index and its componentsAnalyze, predict, and forecast stationary and non-stationary time series processesCreate an event-driven backtesting tool and measure your strategiesBuild a high-frequency algorithmic trading platform with PythonReplicate the CBOT VIX index with SPX options for studying VIX-based strategiesPerform regression-based and classification-based machine learning tasks for predictionUse TensorFlow and Keras in deep learning neural network architectureWho this book is forIf you are a financial or data analyst or a software developer in the financial industry who is interested in using advanced Python techniques for quantitative methods in finance, this is the book you need! You will also find this book useful if you want to extend the functionalities of your existing financial applications by using smart machine learning techniques. Prior experience in Python is required.
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Mathematics Programs
You don′t need to use complicated statistical procedures or fancy research techniques to design, organize, and conduct useful evaluations of your school′s mathematics programs. This guide combines the ease of a do-it-yourself manual with the authority of true experts in the field of educational evaluation. Equipped with this practical manual and an understanding of the importance of evaluation, school administrators can: *Assess the overall quality of the math curriculum *Improve funding by demonstrating student needs *Track enrollment trends and determine the underlying causes *Determine the necessary remedial action to improve test scores This book is part of a seven-volume series for evaluating programs and services in today′s K-12 schools. The "master plan" for this series is found in Evaluating School Programs: An Educator′s Guide by James R. Sanders. It describes the steps involved in conducting the evaluation, including ways to focus the evaluation, identify specific evaluation questions, and collect, organize, analyze, and report the information. All volumes in the series, including this one, are designed to be mutually complementary and used in conjunction with Evaluating School Programs.
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