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Author: Peter D. Kazarinoff Publisher: ISBN: 9781693405419 Category : Languages : en Pages : 348
Book Description
Get started solving problems with the Python programming language!This book introduces some of the most famous scientific libraries for Python: * Python's math and statistics module to do calculations * Matplotlib to build 2D and 3D plots * NumPy to complete calculations on arrays * Jupiter Notebooks to share results with a team * SymPy to solve equations * PySerial to control an Arduino with Python * MicroPython to control an LEDThis book is great for budding engineers and data scientists. The text starts with the basics but finishes with topics rarely included in other engineering and data science programming books like SymPy and PySerial and MicroPython.
Author: Peter D. Kazarinoff Publisher: ISBN: 9781693405419 Category : Languages : en Pages : 348
Book Description
Get started solving problems with the Python programming language!This book introduces some of the most famous scientific libraries for Python: * Python's math and statistics module to do calculations * Matplotlib to build 2D and 3D plots * NumPy to complete calculations on arrays * Jupiter Notebooks to share results with a team * SymPy to solve equations * PySerial to control an Arduino with Python * MicroPython to control an LEDThis book is great for budding engineers and data scientists. The text starts with the basics but finishes with topics rarely included in other engineering and data science programming books like SymPy and PySerial and MicroPython.
Author: Jeeva Jose Publisher: KHANNA PUBLISHING ISBN: 9382609814 Category : Computers Languages : en Pages : 298
Book Description
This book 'Introduction to Computing and Problem Solving with Python' will help every student,teacher and researcher to understand the computing basics and advanced PythonProgramming language. The Python programming topics include the reserved keywords,identifiers, variables, operators, data types and their operations, flowcontrol techniques which include decision making and looping, modules, filesand exception handling techniques. Advanced topics like Python regularexpressions, Database Programming and Object Oriented Programming concepts arealso covered in detail. All chapters have worked out programs, illustrations,review and frequently asked interview questions. The simple style of presentationmakes this a friend for self-learners. More than 300 solved lab exercisesavailable in this book is tested in Python 3.4.3 version for Windows. The book covers syllabus for more than 35 International Universities and45 Indian universities like Dr. APJ Abdul Kalam Technological University,Christ University, Savitribai Phule Pune University, University of Delhi, University of Calicut, Mahatma Gandhi University, University of Mumbai, AICTE, CBSE, MIT, University of Virginia, University of Chicago, University of Toronto, Technical University of Denmark etc.
Author: Bradley N. Miller Publisher: Franklin Beedle & Associates ISBN: 9781590282571 Category : Algorithms Languages : en Pages : 0
Book Description
Thes book has three key features : fundamental data structures and algorithms; algorithm analysis in terms of Big-O running time in introducied early and applied throught; pytohn is used to facilitates the success in using and mastering data strucutes and algorithms.
Author: Peter D. Kazarinoff Publisher: Independently Published ISBN: 9781793814043 Category : Computers Languages : en Pages : 328
Book Description
Get started solving problems with the Python programming language!This book introduces some of the most famous scientific libraries for Python: Python's math and statistics module to do calculationsMatplotlib to build 2D and 3D plotsNumPy to complete calculations on arraysJupiter Notebooks to share results with a teamSymPy to solve equationsPySerial to control an Arduino with PythonMicroPython to control an LEDThis book is great for budding engineers and data scientists. The text starts with the basics but finishes with topics rarely included in other engineering and data science programming books like SymPy and PySerial and MicroPython
Author: Charles R. Severance Publisher: ISBN: 9781530051120 Category : Languages : en Pages : 242
Book Description
Python for Everybody is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.Python is an easy to use and easy to learn programming language that is freely available on Macintosh, Windows, or Linux computers. So once you learn Python you can use it for the rest of your career without needing to purchase any software.This book uses the Python 3 language. The earlier Python 2 version of this book is titled "Python for Informatics: Exploring Information".There are free downloadable electronic copies of this book in various formats and supporting materials for the book at www.pythonlearn.com. The course materials are available to you under a Creative Commons License so you can adapt them to teach your own Python course.
Author: Daniel Zingaro Publisher: No Starch Press ISBN: 1718501331 Category : Computers Languages : en Pages : 392
Book Description
Learn to Code by Solving Problems is a practical introduction to programming using Python. It uses coding-competition challenges to teach you the mechanics of coding and how to think like a savvy programmer. Computers are capable of solving almost any problem when given the right instructions. That’s where programming comes in. This beginner’s book will have you writing Python programs right away. You’ll solve interesting problems drawn from real coding competitions and build your programming skills as you go. Every chapter presents problems from coding challenge websites, where online judges test your solutions and provide targeted feedback. As you practice using core Python features, functions, and techniques, you’ll develop a clear understanding of data structures, algorithms, and other programming basics. Bonus exercises invite you to explore new concepts on your own, and multiple-choice questions encourage you to think about how each piece of code works. You’ll learn how to: Run Python code, work with strings, and use variables Write programs that make decisions Make code more efficient with while and for loops Use Python sets, lists, and dictionaries to organize, sort, and search data Design programs using functions and top-down design Create complete-search algorithms and use Big O notation to design more efficient code By the end of the book, you’ll not only be proficient in Python, but you’ll also understand how to think through problems and tackle them with code. Programming languages come and go, but this book gives you the lasting foundation you need to start thinking like a programmer.
Author: Rubin H. Landau Publisher: John Wiley & Sons ISBN: 3527413154 Category : Science Languages : en Pages : 647
Book Description
The use of computation and simulation has become an essential part of the scientific process. Being able to transform a theory into an algorithm requires significant theoretical insight, detailed physical and mathematical understanding, and a working level of competency in programming. This upper-division text provides an unusually broad survey of the topics of modern computational physics from a multidisciplinary, computational science point of view. Its philosophy is rooted in learning by doing (assisted by many model programs), with new scientific materials as well as with the Python programming language. Python has become very popular, particularly for physics education and large scientific projects. It is probably the easiest programming language to learn for beginners, yet is also used for mainstream scientific computing, and has packages for excellent graphics and even symbolic manipulations. The text is designed for an upper-level undergraduate or beginning graduate course and provides the reader with the essential knowledge to understand computational tools and mathematical methods well enough to be successful. As part of the teaching of using computers to solve scientific problems, the reader is encouraged to work through a sample problem stated at the beginning of each chapter or unit, which involves studying the text, writing, debugging and running programs, visualizing the results, and the expressing in words what has been done and what can be concluded. Then there are exercises and problems at the end of each chapter for the reader to work on their own (with model programs given for that purpose).
Author: John V. Guttag Publisher: MIT Press ISBN: 0262529629 Category : Computers Languages : en Pages : 466
Book Description
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.
Author: Mark Pilgrim Publisher: Apress ISBN: 1430207000 Category : Computers Languages : en Pages : 419
Book Description
* Quick start to learning python—very example oriented approach * Book has its own Web site established by the author: http://diveintopython.org/ Author is well known in the Open Source community and the book has a unique quick approach to learning an object oriented language.