Introduction To Computation And Programming Using Python Second Edition
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Introduction To Computation And Programming Using Python Second Edition
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Author : John V. Guttag
language : en
Publisher: MIT Press
Release Date : 2016-08-08
Introduction To Computation And Programming Using Python Second Edition written by John V. Guttag and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-08 with Computers categories.
The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics.
Introduction To Computation And Programming Using Python
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Author : John V. Guttag
language : en
Publisher: MIT Press
Release Date : 2013-08-09
Introduction To Computation And Programming Using Python written by John V. Guttag and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-09 with Computers categories.
An introductory text that teaches students the art of computational problem solving, covering topics that range from simple algorithms to information visualization.
Introduction To Computation And Programming Using Python Third Edition
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Author : John V. Guttag
language : en
Publisher: MIT Press
Release Date : 2021-01-26
Introduction To Computation And Programming Using Python Third Edition written by John V. Guttag and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-26 with Computers categories.
The new edition of an introduction to the art of computational problem solving using Python. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including numpy, matplotlib, random, pandas, and sklearn. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data as well as substantial material on machine learning. All of the code in the book and an errata sheet are available on the book’s web page on the MIT Press website.
Introduction To Computing And Programming In Python A Multimedia Approach Second Edition
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Author : Barbara Ericson
language : en
Publisher: Prentice Hall
Release Date : 2012
Introduction To Computing And Programming In Python A Multimedia Approach Second Edition written by Barbara Ericson and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
Introduction To Computational Models With Python
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Author : Jose M. Garrido
language : en
Publisher: CRC Press
Release Date : 2015-08-28
Introduction To Computational Models With Python written by Jose M. Garrido and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-28 with Computers categories.
Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python programming language. The book uses the Python programming language interpreter and several packages from the huge Python Library that improve the performance of numerical computing, such as the Numpy and Scipy m
A Student S Guide To Python For Physical Modeling
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Author : Jesse M. Kinder
language : en
Publisher: Princeton University Press
Release Date : 2021-08-03
A Student S Guide To Python For Physical Modeling written by Jesse M. Kinder and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-03 with Science categories.
A fully updated tutorial on the basics of the Python programming language for science students Python is a computer programming language that has gained popularity throughout the sciences. This fully updated second edition of A Student's Guide to Python for Physical Modeling aims to help you, the student, teach yourself enough of the Python programming language to get started with physical modeling. You will learn how to install an open-source Python programming environment and use it to accomplish many common scientific computing tasks: importing, exporting, and visualizing data; numerical analysis; and simulation. No prior programming experience is assumed. This guide introduces a wide range of useful tools, including: Basic Python programming and scripting Numerical arrays Two- and three-dimensional graphics Animation Monte Carlo simulations Numerical methods, including solving ordinary differential equations Image processing Numerous code samples and exercises—with solutions—illustrate new ideas as they are introduced. This guide also includes supplemental online resources: code samples, data sets, tutorials, and more. This edition includes new material on symbolic calculations with SymPy, an introduction to Python libraries for data science and machine learning (pandas and sklearn), and a primer on Python classes and object-oriented programming. A new appendix also introduces command line tools and version control with Git.
Introduction To Computation Programming Using Python
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Author : JOHN V. GUTTAG
language : en
Publisher:
Release Date : 2017
Introduction To Computation Programming Using Python written by JOHN V. GUTTAG and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Test Your Skills In Python Second Edition
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Author : Dr. Shivani Goel
language : en
Publisher: BPB Publications
Release Date : 2022-01-18
Test Your Skills In Python Second Edition written by Dr. Shivani Goel and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-18 with Computers categories.
Best learning Scroll for Python KEY FEATURES ● 16 chapters covering basic (loops) to advanced (NumPy) topics in Python. ● Focus on one topic per chapter to help learners understand topics in depth. ● Key points from Theory highlighted in each chapter for better retention. ● More than 1000 questions that give ample opportunity for practice. ● 7 Model test papers for learners to test their progress. DESCRIPTION This book contains to-the-point theory followed by questions about programming skills in Python. It provides an active and structured way of learning Python. The readers can test their learning by attempting MCQs, True/False questions, and questions about finding the output in a code, identifying the error and much more. The explanations of the answers provide detailed information about the concepts tested. All topics in Python are divided into 16 chapters in this book. These includes Syntax, Input-output, Data types, Strings, Operators and Expressions, Decision Control Statements, Loops, Functions, Lists, Dictionaries, Sets, Tuples, Classes, Files, Graphics, Arrays and Databases. More than 1000 questions are included for all the topics. WHAT YOU WILL LEARN ● Syntax of writing Python programs. ● All possible errors encountered while programming in Python. ● Execution of different constructs in detail. ● Handling graphics and databases in Python. ● Using Arrays in Python. ● Handling programs and files in Python. WHO THIS BOOK IS FOR This book is meant for the students of Undergraduate, postgraduate level and for the beginners in Python. TABLE OF CONTENTS 1. Syntax and Input–Output 2. Data types 3. Strings 4. Operators and Expressions 5. Decision Control statements 6. Loops 7. User- Defined Functions 8. Lists 9. Dictionaries 10. Sets 11. Tuples 12. Classes 13. Files 14. Graphics 15. Arrays (NumPy) 16. Databases Appendix A: Python keywords and their use Appendix B: Operators in Python and their precedence Appendix C: Libraries in Python and common functions Bibliography Model Test Paper 1 (Solved) Model Test Paper 2 (Solved) Model Test Paper 3 (Solved) Model Test Paper 4 (Solved) Model Test Paper 5 (Solved) Model Test Paper 6 (Solved) Model Test Paper 7 (Unsolved)
Making Software
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Author : Andy Oram
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2010-10-14
Making Software written by Andy Oram and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10-14 with Computers categories.
Many claims are made about how certain tools, technologies, and practices improve software development. But which claims are verifiable, and which are merely wishful thinking? In this book, leading thinkers such as Steve McConnell, Barry Boehm, and Barbara Kitchenham offer essays that uncover the truth and unmask myths commonly held among the software development community. Their insights may surprise you. Are some programmers really ten times more productive than others? Does writing tests first help you develop better code faster? Can code metrics predict the number of bugs in a piece of software? Do design patterns actually make better software? What effect does personality have on pair programming? What matters more: how far apart people are geographically, or how far apart they are in the org chart? Contributors include: Jorge Aranda Tom Ball Victor R. Basili Andrew Begel Christian Bird Barry Boehm Marcelo Cataldo Steven Clarke Jason Cohen Robert DeLine Madeline Diep Hakan Erdogmus Michael Godfrey Mark Guzdial Jo E. Hannay Ahmed E. Hassan Israel Herraiz Kim Sebastian Herzig Cory Kapser Barbara Kitchenham Andrew Ko Lucas Layman Steve McConnell Tim Menzies Gail Murphy Nachi Nagappan Thomas J. Ostrand Dewayne Perry Marian Petre Lutz Prechelt Rahul Premraj Forrest Shull Beth Simon Diomidis Spinellis Neil Thomas Walter Tichy Burak Turhan Elaine J. Weyuker Michele A. Whitecraft Laurie Williams Wendy M. Williams Andreas Zeller Thomas Zimmermann
Introduction To Computational Social Science
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Author : Claudio Cioffi-Revilla
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-31
Introduction To Computational Social Science written by Claudio Cioffi-Revilla and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-31 with Computers categories.
This reader-friendly textbook is the first work of its kind to provide a unified Introduction to Computational Social Science (CSS). Four distinct methodological approaches are examined in detail, namely automated social information extraction, social network analysis, social complexity theory and social simulation modeling. The coverage of these approaches is supported by a discussion of the historical context, as well as by a list of texts for further reading. Features: highlights the main theories of the CSS paradigm as causal explanatory frameworks that shed new light on the nature of human and social dynamics; explains how to distinguish and analyze the different levels of analysis of social complexity using computational approaches; discusses a number of methodological tools; presents the main classes of entities, objects and relations common to the computational analysis of social complexity; examines the interdisciplinary integration of knowledge in the context of social phenomena.