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| from math import pi: Introduction to Computing & Problem Solving With PYTHON Jeeva Jose, P.Sojan Lal, 2016-08-01 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. |
| from math import pi: Python All-in-One For Dummies John C. Shovic, Alan Simpson, 2019-04-15 Your one-stop resource on all things Python Thanks to its flexibility, Python has grown to become one of the most popular programming languages in the world. Developers use Python in app development, web development, data science, machine learning, and even in coding education classes. There's almost no type of project that Python can't make better. From creating apps to building complex websites to sorting big data, Python provides a way to get the work done. Python All-in-One For Dummies offers a starting point for those new to coding by explaining the basics of Python and demonstrating how it’s used in a variety of applications. Covers the basics of the language Explains its syntax through application in high-profile industries Shows how Python can be applied to projects in enterprise Delves into major undertakings including artificial intelligence, physical computing, machine learning, robotics and data analysis This book is perfect for anyone new to coding as well as experienced coders interested in adding Python to their toolbox. |
| from math import pi: The Python Code Nitin, Ankit Kumar, Anmol Sharma, Utkarsh Kumar, 2023-06-13 The Python Code - Practical Book On Python Programming For Beginners The Python Code is one of the best books on Python Programming, we aim to provide a comprehensive introduction to the basics of programming using Python. This book is perfect for beginners who are new to programming and wish to learn the fundamentals of Python. This book is intended for individuals who want to embark on a journey with programming and specifically with Python. Whether you are a beginner who is just starting or an experienced programmer looking to brush up on your Python skills, this book has something to offer. This book contains daily life problems that will help you understand the concepts of Python in a better way. It contains diagrams and examples to simplify the learning process, also there are numerous questions to practice the topic in each section. The book is structured to take you through the core concepts of Python programming, starting from the basics and gradually building up to more advanced topics. We cover everything from variables and data types to loops and functions in Python. We believe that learning by doing is the best way to master a new skill. By working through these examples, you will be able to solidify your understanding of Python and gain confidence in your programming skills. Overall, this book is for anyone interested in learning, using, or revising Python, regardless of their level of expertise. |
| from math import pi: Python Essentials For Dummies John C. Shovic, Alan Simpson, 2024-03-27 The no-nonsense way to get started coding in the Python programming language Python Essentials For Dummies is a quick reference to all the core concepts in Python, the multifaceted general-purpose language used for everything from building websites to creating apps. This book gets right to the point, with no excess review, wordy explanations, or fluff, making it perfect as a desk reference on the job or as a brush-up as you expand your skills in related areas. Focusing on just the essential topics you need to know to brush up or level up your Python skill, this is the reliable little book you can always turn to for answers. Get a quick and thorough intro to the basic concepts of coding in Python Review what you've already learned or pick up essential new skills Create websites, software, machine learning, and automation for school or work Keep this concise reference book handy for jogging your memory as you code This portable Dummies Essentials book focuses on the key topics you need to know about the popular Python language. Great for supplementing a course, reviewing for a certification, or staying knowledgeable on the job. |
| from math import pi: Python 101 Michael Driscoll, 2014-06-03 Learn how to program with Python from beginning to end. This book is for beginners who want to get up to speed quickly and become intermediate programmers fast! |
| from math import pi: Python for Finance Yuxing Yan, 2014-04-25 A hands-on guide with easy-to-follow examples to help you learn about option theory, quantitative finance, financial modeling, and time series using Python. Python for Finance is perfect for graduate students, practitioners, and application developers who wish to learn how to utilize Python to handle their financial needs. Basic knowledge of Python will be helpful but knowledge of programming is necessary. |
| from math import pi: Programming for Computations - Python Svein Linge, Hans Petter Langtangen, 2016-07-25 This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows the students to write simple programs for solving common mathematical problems with numerical methods in engineering and science courses. The emphasis is on generic algorithms, clean design of programs, use of functions, and automatic tests for verification. |
| from math import pi: Python for Data Science Ted Wolf, 2022-04-26 Are you looking for a Python for Data Science crash course and want to come up easily with your first project from scratch in no time? Are you constantly looking for information on social networks (like FB groups) and you don't know where to start with Python programming? If so, then read on! Python is often used in data science today because it is a mature programming language that has excellent properties for beginning programmers. Some of the most notable of these properties are the easy-to-read password, suppression of optional delimiters, dynamic writing, and the use of dynamic memory. Data science uses science strategies to process data and separate information from it. It moves away from an idea similar to Big Data and Data Mining. It requires innovative equipment along with useful calculation and programming to deal with data problems or process data to gain substantial learning from them. The improvement and highly useful research in the world of Computing and Technology have increased the importance of its most basic and essential concepts in a thousand aspects. This notion of principle is what we continuously refer to as data, and that data is the only thing that opens the way for everything in the world. The world's largest organizations and companies have built their creation and their philosophies and determine a unique portion of their pay through data. The value and importance of data can be understood with the simple certainty that a legitimate data storage/distribution center is a million times more profitable than the pure gold mine in the advanced world. However, learning all the required skills to master data science and machine learning could certainly be challenging. BUT DON’T WORRY: In this complete Guide we have condensed all the knowledge you need in a simple and practical way. Through his revolutionary and systematic approach, you will skyrocket your skills, regardless of your previous experience, with the best techniques to manipulate and process datasets, learn in deep the principles of Python programming, and their real-world applications. In this book you are ready to discover: · How to move your first steps in the world of “Python”. I will explain you, with easy to follow visuals, how to exactly install Python on the Mac OS X , Windows and Linux systems. · How to easily setting up your first Data Science project from scratch with Python in less than 7 days. · Practical codes and exercises to use Python. I will explain you the step-by-step process to create games like: “magic 8 ball” and “hangman game”. · How works the regression algorithms used in data science and what are the best tips and tricks to work with them. · How Scikit-Learn library is used in the development of a machine learning algorithm. · And much more! Even if you're still a beginner struggling on how to start projects with Python, this book will surely give you the right information to skyrocket your programming skills to the next level. Keep in mind: “Real progress happens only when advantages of a new technology become available to everybody” (H. Ford). Pick up your own copy today by clicking the BUY NOW button at the top of the page! |
| from math import pi: Essential Python for the Physicist Giovanni Moruzzi, 2020-06-02 This book introduces the reader with little or no previous computer-programming experience to the Python programming language of interest for a physicist or a natural-sciences student. The book starts with basic interactive Python in order to acquire an introductory familiarity with the language, than tackle Python scripts (programs) of increasing complexity, that the reader is invited to run on her/his computer. All program listings are discussed in detail, and the reader is invited to experiment on what happens if some code lines are modified. The reader is introduced to Matplotlib graphics for the generation of figures representing data and function plots and, for instance, field lines. Animated function plots are also considered. A chapter is dedicated to the numerical solution of algebraic and transcendental equations, the basic mathematical principles are discussed and the available Python tools for the solution are presented. A further chapter is dedicated to the numerical solution of ordinary differential equations. This is of vital importance for the physicist, since differential equations are at the base of both classical physics (Newton’s equations) and quantum mechanics (Schroedinger’s equation). The shooting method for the numerical solution of ordinary differential equations with boundary conditions at two boundaries is also presented. Python programs for the solution of two quantum-mechanics problems are discussed as examples. Two chapters are dedicated to Tkinter graphics, which gives the user more freedom than Matplotlib, and to Tkinter animation. Programs displaying the animation of physical problems involving the solution of ordinary differential equations (for which in most cases there is no algebraic solution) in real time are presented and discussed. Finally, 3D animation is presented with Vpython. |
| from math import pi: Internet of Things Jeeva Jose, Internet of Things (IoT) is a network comprising of machines, vehicles, home appliances, computers, micro controllers, sensors and actuators supported by application software and protocols. The study of IoT is the detailed understanding of these components. As per the estimates, by 2020 the connected things in IoT network will outnumber human beings in earth. Practical applications of IoT Technology is in every area like agriculture, construction management, health care, energy, transportation, education etc. The opportunity in business and job for IoT is increasing day by day. |
| from math import pi: Data Structures and Algorithms in Python Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser, 2013-06-17 Based on the authors' market leading data structures books in Java and C++, this book offers a comprehensive, definitive introduction to data structures in Python by authoritative authors. Data Structures and Algorithms in Python is the first authoritative object-oriented book available for Python data structures. Designed to provide a comprehensive introduction to data structures and algorithms, including their design, analysis, and implementation, the text will maintain the same general structure as Data Structures and Algorithms in Java and Data Structures and Algorithms in C++. Begins by discussing Python's conceptually simple syntax, which allows for a greater focus on concepts. Employs a consistent object-oriented viewpoint throughout the text. Presents each data structure using ADTs and their respective implementations and introduces important design patterns as a means to organize those implementations into classes, methods, and objects. Provides a thorough discussion on the analysis and design of fundamental data structures. Includes many helpful Python code examples, with source code provided on the website. Uses illustrations to present data structures and algorithms, as well as their analysis, in a clear, visual manner. Provides hundreds of exercises that promote creativity, help readers learn how to think like programmers, and reinforce important concepts. Contains many Python-code and pseudo-code fragments, and hundreds of exercises, which are divided into roughly 40% reinforcement exercises, 40% creativity exercises, and 20% programming projects. |
| from math import pi: Pyomo — Optimization Modeling in Python William E. Hart, Carl D. Laird, Jean-Paul Watson, David L. Woodruff, Gabriel A. Hackebeil, Bethany L. Nicholson, John D. Siirola, 2017-05-26 This book provides a complete and comprehensive guide to Pyomo (Python Optimization Modeling Objects) for beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. Using many examples to illustrate the different techniques useful for formulating models, this text beautifully elucidates the breadth of modeling capabilities that are supported by Pyomo and its handling of complex real-world applications. This second edition provides an expanded presentation of Pyomo’s modeling capabilities, providing a broader description of the software that will enable the user to develop and optimize models. Introductory chapters have been revised to extend tutorials; chapters that discuss advanced features now include the new functionalities added to Pyomo since the first edition including generalized disjunctive programming, mathematical programming with equilibrium constraints, and bilevel programming. Pyomo is an open source software package for formulating and solving large-scale optimization problems. The software extends the modeling approach supported by modern AML (Algebraic Modeling Language) tools. Pyomo is a flexible, extensible, and portable AML that is embedded in Python, a full-featured scripting language. Python is a powerful and dynamic programming language that has a very clear, readable syntax and intuitive object orientation. Pyomo includes Python classes for defining sparse sets, parameters, and variables, which can be used to formulate algebraic expressions that define objectives and constraints. Moreover, Pyomo can be used from a command-line interface and within Python's interactive command environment, which makes it easy to create Pyomo models, apply a variety of optimizers, and examine solutions. |
| from math import pi: Python Programming Dr.L.Ramesh, Dr.R.Suresh, Dr.S.Gopinathan, 2024-01-02 Dr.L.Ramesh, Assistant Professor, Department of Information Technology, Vels Institute of Science, Technology & Advanced Studies (VISTAS),Pallavaram, Chennai, Tamil Nadu, India. Dr.R.Suresh, Assistant Professor, Department of Computer Applications, DRBCCC Hindu College, Pattabiram, Chennai, Tamil Nadu, India. Dr.S.Gopinathan, Professor & Head, Department of Computer Science, Guindy Campus, University of Madras, Chennai, Tamil Nadu, India. |
| from math import pi: A Primer on Scientific Programming with Python Hans Petter Langtangen, 2016-07-28 The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches Matlab-style and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. ... Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010 Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” John D. Cook, The Mathematical Association of America, September 2011 This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science. Alex Small, IEEE, CiSE Vol. 14 (2), March /April 2012 “This fourth edition is a wonderful, inclusive textbook that covers pretty much everything one needs to know to go from zero to fairly sophisticated scientific programming in Python...” Joan Horvath, Computing Reviews, March 2015 |
| from math import pi: PYTHON ESSENTIALS Mr. Ajay Gupta, Dr. Prabhat Kumar Srivastava, Ms. Mamta Srivastava, Mrs. Priya Gupta, The book titled Python Essentials' covers complete syllabus of Concept of Python Programming prescribed by Technical University of Uttar Pradesh and other Universities also. This book builds on the concepts of Python programming language introduced in Several Class. The book is replete with a rich pedagogy comprising true-or-false, multiple-choice apart from programming problems of varying difficulty levels to help students ace their exams with ease. Amply supported by illustrative diagrams, keywords and topic highlights, this book is an ideal text that helps students build a firm foundation in the subject The book titled Python Essentials' covers complete syllabus of Concept of Python Programming prescribed by Technical University of Uttar Pradesh and other Universities also. This book builds on the concepts of Python programming language introduced in Class XI. The book is replete with a rich pedagogy comprising true-or-false, multiple-choice apart from programming problems of varying difficulty levels to help students ace their exams with ease. Amply supported by illustrative diagrams, keywords and topic highlights, this book is an ideal text that helps students build a firm foundation in the subject. |
| from math import pi: Python Programming for Biology Tim J. Stevens, Wayne Boucher, 2015-02-12 Do you have a biological question that could be readily answered by computational techniques, but little experience in programming? Do you want to learn more about the core techniques used in computational biology and bioinformatics? Written in an accessible style, this guide provides a foundation for both newcomers to computer programming and those interested in learning more about computational biology. The chapters guide the reader through: a complete beginners' course to programming in Python, with an introduction to computing jargon; descriptions of core bioinformatics methods with working Python examples; scientific computing techniques, including image analysis, statistics and machine learning. This book also functions as a language reference written in straightforward English, covering the most common Python language elements and a glossary of computing and biological terms. This title will teach undergraduates, postgraduates and professionals working in the life sciences how to program with Python, a powerful, flexible and easy-to-use language. |
| from math import pi: Python and Matplotlib Essentials for Scientists and Engineers Matt A Wood, 2015-06-01 This book provides an introduction to the core features of the Python programming language and Matplotlib plotting routings for scientists and engineers (or students of either discipline) who want to use PythonTM to analyse data, simulate physical processes, and render publication-quality plots. No previous programming experience is needed before reading the first page. Readers will learn the core features of the Python programming language in under a day. They will be able to immediately use Python to implement codes that solve their own problems and make beautiful plots and animations. Python code is extremely fast to prototype, allowing users to achieve results quickly and accurately. The examples within the book are available for download at http://pythonessentials.com. Python and Matplotlib Essentials for Scientists and Engineers is accessible for motivated high-school students, but will likely be most useful for undergraduate and graduate students as well as working professionals who have some background with the basic mathematical concepts. This book is intended for technical people who want to get things done. |
| from math import pi: Managing Your Biological Data with Python Allegra Via, Kristian Rother, Anna Tramontano, 2014-03-18 Take Control of Your Data and Use Python with Confidence Requiring no prior programming experience, Managing Your Biological Data with Python empowers biologists and other life scientists to work with biological data on their own using the Python language. The book teaches them not only how to program but also how to manage their data. It shows how to read data from files in different formats, analyze and manipulate the data, and write the results to a file or computer screen. The first part of the text introduces the Python language and teaches readers how to write their first programs. The second part presents the basic elements of the language, enabling readers to write small programs independently. The third part explains how to create bigger programs using techniques to write well-organized, efficient, and error-free code. The fourth part on data visualization shows how to plot data and draw a figure for an article or slide presentation. The fifth part covers the Biopython programming library for reading and writing several biological file formats, querying the NCBI online databases, and retrieving biological records from the web. The last part provides a cookbook of 20 specific programming recipes, ranging from secondary structure prediction and multiple sequence alignment analyses to superimposing protein three-dimensional structures. Tailoring the programming topics to the everyday needs of biologists, the book helps them easily analyze data and ultimately make better discoveries. Every piece of code in the text is aimed at solving real biological problems. |
| from math import pi: Python for Engineers Robert Johnson, 2024-10-25 Python for Engineers: Solving Real-World Technical Challenges is a comprehensive guide crafted for engineers who seek to leverage Python's capabilities in addressing complex technical problems. This meticulously structured book serves as a valuable resource for both beginners and seasoned programmers, offering clarity and depth across essential Python concepts that are pivotal in various engineering domains. From setting up the development environment to mastering core syntax and data types, each chapter builds on the previous, ensuring a well-rounded understanding of Python's robust capabilities. Delving deeper, the book covers advanced topics such as object-oriented programming, error handling, and the integration of powerful libraries and modules. Readers will gain practical insights into data handling, web development, and task automation, equipping them with the tools necessary for efficient and effective software development. By emphasizing both foundational skills and applied strategies, Python for Engineers empowers its readers to harness Python's potential, driving innovation and technical excellence in their engineering projects. |
| from math import pi: Python Essentials 2: Aligned with PCAP Certified Associate in Python Programming The OpenEDG Python Institute, 2023-08-22 Immerse yourself in some of the more advanced Python concepts, master Object-Oriented Programming, and gear up for the prestigious PCAP™ – Certified Associate Python Programmer certification. By the end of this book, you'll be equipped with the expertise to carry out more sophisticated Software Development, Security, Networking, IoT, and engineering roles. Additionally, this book will prepare you to tackle the PCAP qualification exam and take your programming skills to the next level. Being PCAP qualified means that both employers and your fellow programmers will be able to recognize your programming aptitude and rely on you to get jobs done. Python Essentials 2 takes you through some of the more advanced Python concepts and arms you with skills such as: Algorithmic and Analytical Thinking, to help you design and create your own applications Multi-Module Application Development and Debugging, to ensure that your coding skills are second-to-none Best Programming Practices of Python Professionals Solutions Architecture, so that you can successfully scale up your projects, collaborate with other programmers, and consistently deliver high-performing code Object-Oriented Programming, to ensure that your software is robust and adheres to the latest industry standards. This book builds upon your knowledge from Python Essentials 1, covering advanced techniques such as modules, packages, exceptions, file processing, and object-oriented programming. By learning these skills, you will become a proficient Python programmer and a valued member of the Python Programming Community, well-equipped to handle complex projects and codebases. With 24 chapters split into four parts, 22 lab exercises with hints and sample solutions and 23 quizzes, this book sets you on the path to becoming a certified python programmer. Elevate your coding prowess for future success; embark on your next Python journey now. |
| from math import pi: Introduction to Python and Large Language Models Dilyan Grigorov, |
| from math import pi: Explorations in Computing John S. Conery, 2014-09-24 An Active Learning Approach to Teaching the Main Ideas in Computing Explorations in Computing: An Introduction to Computer Science and Python Programming teaches computer science students how to use programming skills to explore fundamental concepts and computational approaches to solving problems. Tbook gives beginning students an introduction to |
| from math import pi: Learning Scientific Programming with Python Christian Hill, 2020-11-12 Learn to master basic programming tasks from scratch with real-life, scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commercial packages and this fast-paced introduction moves from the basics to advanced concepts in one complete volume, enabling readers to gain proficiency quickly. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving on to the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualization, this textbook also discusses the use of Jupyter Notebooks to build rich-media, shareable documents for scientific analysis. The second edition features a new chapter on data analysis with the pandas library and comprehensive updates, and new exercises and examples. A final chapter introduces more advanced topics such as floating-point precision and algorithm stability, and extensive online resources support further study. This textbook represents a targeted package for students requiring a solid foundation in Python programming. |
| from math import pi: Hands-on Supervised Learning with Python Gnana Lakshmi T C, Madeleine Shang, 2021-01-06 Hands-On ML problem solving and creating solutions using Python KEY FEATURES _Introduction to Python Programming _Python for Machine Learning _Introduction to Machine Learning _Introduction to Predictive Modelling, Supervised and Unsupervised Algorithms _Linear Regression, Logistic Regression and Support Vector MachinesÊ DESCRIPTIONÊ You will learn about the fundamentals of Machine Learning and Python programming post, which you will be introduced to predictive modelling and the different methodologies in predictive modelling. You will be introduced to Supervised Learning algorithms and Unsupervised Learning algorithms and the difference between them.Ê We will focus on learning supervised machine learning algorithms covering Linear Regression, Logistic Regression, Support Vector Machines, Decision Trees and Artificial Neural Networks. For each of these algorithms, you will work hands-on with open-source datasets and use python programming to program the machine learning algorithms. You will learn about cleaning the data and optimizing the features to get the best results out of your machine learning model. You will learn about the various parameters that determine the accuracy of your model and how you can tune your model based on the reflection of these parameters. WHAT WILL YOU LEARN _Get a clear vision of what is Machine Learning and get familiar with the foundation principles of Machine learning. _Understand the Python language-specific libraries available for Machine learning and be able to work with those libraries. _Explore the different Supervised Learning based algorithms in Machine Learning and know how to implement them when a real-time use case is presented to you. _Have hands-on with Data Exploration, Data Cleaning, Data Preprocessing and Model implementation. _Get to know the basics of Deep Learning and some interesting algorithms in this space. _Choose the right model based on your problem statement and work with EDA techniques to get good accuracy on your model WHO THIS BOOK IS FOR This book is for anyone interested in understanding Machine Learning. Beginners, Machine Learning Engineers and Data Scientists who want to get familiar with Supervised Learning algorithms will find this book helpful. TABLE OF CONTENTS Ê1. ÊIntroduction to Python Programming Ê2. Python for Machine LearningÊÊÊÊÊ Ê3.Ê Introduction to Machine LearningÊÊÊÊÊÊÊÊÊ Ê4. Supervised Learning and Unsupervised LearningÊÊÊÊÊÊÊÊÊ Ê5. Linear Regression: A Hands-on guideÊÊÊ Ê6. Logistic Regression Ð An Introduction Ê7. A sneak peek into the working of Support Vector machines(SVM)ÊÊÊÊÊÊ Ê8. Decision Trees Ê9. Random Forests Ê10. ÊTime Series models in Machine Learning Ê11.Ê Introduction to Neural Networks Ê12. ÊÊÊRecurrent Neural Networks Ê13. ÊÊÊConvolutional Neural Networks Ê14. ÊÊÊPerformance Metrics Ê15. ÊÊÊIntroduction to Design Thinking Ê16. Ê Design Thinking Case Study |
| from math import pi: Python and Algorithmic Thinking for the Complete Beginner Aristides Bouras, 2024-06-14 Unlock the power of Python with this comprehensive guide, “Python and Algorithmic Thinking for the Complete Beginner.” It covers everything from computer basics to advanced decision and loop control structures. Key Features Comprehensive coverage from basic computer operations to advanced programming concepts Step-by-step progression of each topic, along with tips and tricks to enhance coding efficiency In-depth exploration of Python and algorithmic thinking with exercises and practical examples Book DescriptionThis course is meticulously designed to take beginners on a journey through the fascinating world of Python programming and algorithmic thinking. The initial chapters lay a strong foundation, starting with the basics of how computers operate, moving into Python programming, and familiarizing learners with integrated development environments like IDLE and Visual Studio Code. Further, the course delves into essential programming constructs such as variables, constants, input/output handling, and operators. You'll gain practical experience with trace tables, sequence control structures, and decision control structures through comprehensive exercises and examples. The curriculum emphasizes hands-on learning with chapters dedicated to manipulating numbers, strings, and understanding complex mathematical expressions. By mastering these concepts, you'll be well-prepared to tackle more advanced topics. The final chapters introduce you to object-oriented programming and file manipulation, rounding out your skill set. Throughout the course, practical tips and tricks are provided to enhance your coding efficiency and problem-solving skills. By the end of this course, you will have a robust understanding of Python programming and the ability to apply algorithmic thinking to solve real-world problems.What you will learn Understand how computers work and the basics of Python programming Install and use integrated development environments (IDEs) Develop skills in decision and loop control structures Manipulate data using lists, dictionaries, and strings Apply algorithmic thinking to solve complex problems Gain proficiency in object-oriented programming & file manipulation Who this book is for This course is ideal for absolute beginners with no prior programming experience. Basic computer literacy is required, but no specific knowledge of programming or algorithms is necessary. It is also suitable for individuals looking to refresh their Python skills and enhance their understanding of algorithmic thinking. High school and college students interested in programming, professionals seeking to upskill, and hobbyists eager to learn a new programming language will all find value in this course. |
| from math import pi: Data Science for Neuroimaging Ariel Rokem, Tal Yarkoni, 2023-11-07 Data science methods and tools—including programming, data management, visualization, and machine learning—and their application to neuroimaging research As neuroimaging turns toward data-intensive discovery, researchers in the field must learn to access, manage, and analyze datasets at unprecedented scales. Concerns about reproducibility and increased rigor in reporting of scientific results also demand higher standards of computational practice. This book offers neuroimaging researchers an introduction to data science, presenting methods, tools, and approaches that facilitate automated, reproducible, and scalable analysis and understanding of data. Through guided, hands-on explorations of openly available neuroimaging datasets, the book explains such elements of data science as programming, data management, visualization, and machine learning, and describes their application to neuroimaging. Readers will come away with broadly relevant data science skills that they can easily translate to their own questions. • Fills the need for an authoritative resource on data science for neuroimaging researchers • Strong emphasis on programming • Provides extensive code examples written in the Python programming language • Draws on openly available neuroimaging datasets for examples • Written entirely in the Jupyter notebook format, so the code examples can be executed, modified, and re-executed as part of the learning process |
| from math import pi: Introduction to Scientific Programming with Python Joakim Sundnes, 2020 This open access book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and example-based, making it suitable for students and researchers with little or no prior experience in programming. The book uses relevant examples from mathematics and the natural sciences to present programming as a practical toolbox that can quickly enable readers to write their own programs for data processing and mathematical modeling. These tools include file reading, plotting, simple text analysis, and using NumPy for numerical computations, which are fundamental building blocks of all programs in data science and computational science. At the same time, readers are introduced to the fundamental concepts of programming, including variables, functions, loops, classes, and object-oriented programming. Accordingly, the book provides a sound basis for further computer science and programming studies. |
| from math import pi: Programming in Python Pooja Sharma, 2020-04-09 An interactive way to introduce the world of Python Programming KEY FEATURES Detailed comparisons and differentiation of python language from other most popular languages C/C++/Java. Authentic and extensive set of programming illustrations in every chapter of the book. Broad study on all the programming constructs of the python programming language such as native data types, looping, decision making, exception handling, file handling etc. Broad study of Python Object Oriented Programming features with illustrations. Numerous review questions and exercises at the end of every chapter. DESCRIPTION This Book is meant for wide range of readers who wish to learn the basics of Python programming language. It can be helpful for students, programmers, researchers, and software developers. The basic concepts of python programming are dealt in detail. The various concepts of python language such as object-oriented features, operators, native data types, control structures, functions, exception handling, file handling, etc are discussed in detail with the authentic programming illustration of each. presently, python programming is a hot topic among academicianÕs researchers, and program developers. As a result, the book is designed to give an in-depth knowledge of programming in python. This book can be used as handbook as well as a guide for students of all computer science stream at any grade beginning from 10+1 to Research in PhD. To conclude, we hope that the readers will find this book a helpful guide and valuable source of information about python programming. WHAT WILL YOU LEARN Python Data Types, Input Output Operators and Expressions Control Structures Python Functions, Modules Exception Handling File Management, Classes and Objects Inheritance, Python Operator Overloading Ê WHO THIS BOOK IS FOR Students, Programmers, researchers, and software developers who wish to learn the basics of Python programming language. Ê Table of Contents 1. Introduction to Python Language 2. Python Data Types and Input Output 3. Operators and Expressions 4. Control Structures 5. Python Native Data Types 6. Python Functions 7. Python Modules 8. Exception Handling 9. File Management in Python 10. Classes and Objects 11. Inheritance 12. Python Operator Overloading |
| from math import pi: Math for Programmers Paul Orland, 2021-01-12 In Math for Programmers you’ll explore important mathematical concepts through hands-on coding. Filled with graphics and more than 300 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest fields. As you tackle the basics of linear algebra, calculus, and machine learning, you’ll master the key Python libraries used to turn them into real-world software applications. Summary To score a job in data science, machine learning, computer graphics, and cryptography, you need to bring strong math skills to the party. Math for Programmers teaches the math you need for these hot careers, concentrating on what you need to know as a developer. Filled with lots of helpful graphics and more than 200 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest programming fields. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Skip the mathematical jargon: This one-of-a-kind book uses Python to teach the math you need to build games, simulations, 3D graphics, and machine learning algorithms. Discover how algebra and calculus come alive when you see them in code! About the book In Math for Programmers you’ll explore important mathematical concepts through hands-on coding. Filled with graphics and more than 300 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest fields. As you tackle the basics of linear algebra, calculus, and machine learning, you’ll master the key Python libraries used to turn them into real-world software applications. What's inside Vector geometry for computer graphics Matrices and linear transformations Core concepts from calculus Simulation and optimization Image and audio processing Machine learning algorithms for regression and classification About the reader For programmers with basic skills in algebra. About the author Paul Orland is a programmer, software entrepreneur, and math enthusiast. He is co-founder of Tachyus, a start-up building predictive analytics software for the energy industry. You can find him online at www.paulor.land. Table of Contents 1 Learning math with code PART I - VECTORS AND GRAPHICS 2 Drawing with 2D vectors 3 Ascending to the 3D world 4 Transforming vectors and graphics 5 Computing transformations with matrices 6 Generalizing to higher dimensions 7 Solving systems of linear equations PART 2 - CALCULUS AND PHYSICAL SIMULATION 8 Understanding rates of change 9 Simulating moving objects 10 Working with symbolic expressions 11 Simulating force fields 12 Optimizing a physical system 13 Analyzing sound waves with a Fourier series PART 3 - MACHINE LEARNING APPLICATIONS 14 Fitting functions to data 15 Classifying data with logistic regression 16 Training neural networks |
| from math import pi: Statistics, Data Mining, and Machine Learning in Astronomy Željko Ivezić, Andrew J. Connolly, Jacob T. VanderPlas, Alexander Gray, 2014-01-12 As telescopes, detectors, and computers grow ever more powerful, the volume of data at the disposal of astronomers and astrophysicists will enter the petabyte domain, providing accurate measurements for billions of celestial objects. This book provides a comprehensive and accessible introduction to the cutting-edge statistical methods needed to efficiently analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the upcoming Large Synoptic Survey Telescope. It serves as a practical handbook for graduate students and advanced undergraduates in physics and astronomy, and as an indispensable reference for researchers. Statistics, Data Mining, and Machine Learning in Astronomy presents a wealth of practical analysis problems, evaluates techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. For all applications described in the book, Python code and example data sets are provided. The supporting data sets have been carefully selected from contemporary astronomical surveys (for example, the Sloan Digital Sky Survey) and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, evaluate the methods, and adapt them to their own fields of interest. Describes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data sets Features real-world data sets from contemporary astronomical surveys Uses a freely available Python codebase throughout Ideal for students and working astronomers |
| from math import pi: Oswaal CBSE Question Bank Class 12 Computer Science, Chapterwise and Topicwise Solved Papers For Board Exams 2025 Oswaal Editorial Board, 2024-01-23 Description of the product: • 100% Updated Syllabus & Fully Solved Board Papers: we have got you covered with the latest and 100% updated curriculum. • Crisp Revision with Topic-wise Revision Notes, Smart Mind Maps & Mnemonics. • Extensive Practice with 3000+ Questions & Board Marking Scheme Answers to give you 3000+ chances to become a champ. • Concept Clarity with 1000+ Concepts & 50+ Concept Videos for you to learn the cool way—with videos and mind-blowing concepts. • NEP 2020 Compliance with Art Integration & Competency-Based Questions for you to be on the cutting edge of the coolest educational trends. |
| from math import pi: Understanding Optics with Python Vasudevan Lakshminarayanan, Hassen Ghalila, Ahmed Ammar, L. Srinivasa Varadharajan, 2018-02-19 Optics is an enabling science that forms a basis for our technological civilization. Courses in optics are a required part of the engineering or physics undergraduate curriculum in many universities worldwide. The aim of Understanding Optics with Python is twofold: first, to describe certain basic ideas of classical physical and geometric optics; second, to introduce the reader to computer simulations of physical phenomena. The text is aimed more broadly for those who wish to use numerical/computational modeling as an educational tool that promotes interactive teaching (and learning). In addition, it offers an alternative to developing countries where the necessary equipment to carry out the appropriate experiments is not available as a result of financial constraints. This approach contributes to a better diffusion of knowledge about optics. The examples given in this book are comparable to those found in standard textbooks on optics and are suitable for self-study. This text enables the user to study and understand optics using hands-on simulations with Python. Python is our programming language of choice because of its open-source availability, extensive functionality, and an enormous online support. Essentials of programming in Python 3.x, including graphical user interface, are also provided. The codes in the book are available for download on the book’s website. Discusses most standard topics of traditional physical and geometrical optics through Python and PyQt5 Provides visualizations and in-depth descriptions of Python’s programming language and simulations Includes simulated laboratories where students are provided a hands-on exploration of Python software Coding and programming featured within the text are available for download on the book’s corresponding website. Understanding Optics with Python by Vasudevan Lakshminarayanan, Hassen Ghalila, Ahmed Ammar, and L. Srinivasa Varadharajan is born around a nice idea: using simulations to provide the students with a powerful tool to understand and master optical phenomena. The choice of the Python language is perfectly matched with the overall goal of the book, as the Python language provides a completely free and easy-to-learn platform with huge cross-platform compatibility, where the reader of the book can conduct his or her own numerical experiments to learn faster and better. — Costantino De Angelis, University of Brescia, Italy Teaching an important programming language like Python through concrete examples from optics is a natural and, in my view, very effective approach. I believe that this book will be used by students and appreciated greatly by instructors. The topic of modelling optical effects and systems where the students should already have a physical background provides great motivation for students to learn the basics of a powerful programming language without the intimidation factor that often goes with a formal computer science course. — John Dudley, FEMTO-ST Institute, Besançon, France |
| from math import pi: Supercharged Python Brian Overland, John Bennett, 2019-06-19 “Brian Overland makes programming simple. . . . To my amazement, his books explain complicated code clearly enough for anyone to understand.” —Art Sedighi, PhD Tapping into the full power of Python doesn’t have to be difficult. Supercharged Python is written for people who’ve learned the fundamentals of the language but want to take their skills to the next level. After a quick review of Python, the book covers: advanced list and string techniques; all the ways to handle text and binary files; financial applications; advanced techniques for writing classes; generators and decorators; and how to master packages such as Numpy (Numeric Python) to supercharge your applications! Use profilers and “magic methods” to code like a pro Harness the power of regular expressions to process text quickly with a single statement Take advantage of 22 coding shortcuts, along with performance tips, to save time and optimize your code Create really useful classes and objects, for games, simulations, money, mathematics, and more Use multiple modules to build powerful apps while avoiding the “gotchas” Import packages to dramatically speed up statistical operations—by as much as 100 times! Refer to the five-part language reference to look up fine points of the language Supercharged Python demonstrates techniques that allow you to write faster and more powerful code, whether you’re manipulating large amounts of data or building sophisticated applications. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details. |
| from math import pi: Long Short-Term Memory Networks With Python Jason Brownlee, 2017-07-20 The Long Short-Term Memory network, or LSTM for short, is a type of recurrent neural network that achieves state-of-the-art results on challenging prediction problems. In this laser-focused Ebook, finally cut through the math, research papers and patchwork descriptions about LSTMs. Using clear explanations, standard Python libraries and step-by-step tutorial lessons you will discover what LSTMs are, and how to develop a suite of LSTM models to get the most out of the method on your sequence prediction problems. |
| from math import pi: Quantum Algorithms for Cryptographically Significant Boolean Functions Tharrmashastha SAPV, Debajyoti Bera, Arpita Maitra, Subhamoy Maitra, 2021-07-19 This book is a timely report of the state-of-the-art analytical techniques in the domain of quantum algorithms related to Boolean functions. It bridges the gap between recent developments in the area and the hands-on analysis of the spectral properties of Boolean functions from a cryptologic viewpoint. Topics covered in the book include Qubit, Deutsch–Jozsa and Walsh spectrum, Grover’s algorithm, Simon’s algorithm and autocorrelation spectrum. The book aims at encouraging readers to design and implement practical algorithms related to Boolean functions. Apart from combinatorial techniques, this book considers implementing related programs in a quantum computer. Researchers, practitioners and educators will find this book valuable. |
| from math import pi: Numerical Methods in Engineering with Python 3 Jaan Kiusalaas, 2013-01-21 Provides an introduction to numerical methods for students in engineering. It uses Python 3, an easy-to-use, high-level programming language. |
| from math import pi: Python Power! Matthew A. Telles, 2008 A guide to the Python computer language covers such topics as data types, control flow, functions and modules, exception handling, the GUI library, and input and output functionality. |
| from math import pi: Numerical Methods in Engineering with Python Jaan Kiusalaas, 2010-01-29 This text is for engineering students and a reference for practising engineers, especially those who wish to explore Python. This new edition features 18 additional exercises and the addition of rational function interpolation. Brent's method of root finding was replaced by Ridder's method, and the Fletcher-Reeves method of optimization was dropped in favor of the downhill simplex method. Each numerical method is explained in detail, and its shortcomings are pointed out. The examples that follow individual topics fall into two categories: hand computations that illustrate the inner workings of the method and small programs that show how the computer code is utilized in solving a problem. This second edition also includes more robust computer code with each method, which is available on the book website. This code is made simple and easy to understand by avoiding complex bookkeeping schemes, while maintaining the essential features of the method. |
| from math import pi: A Functional Start to Computing with Python Ted Herman, 2013-07-26 A Functional Start to Computing with Python enables students to quickly learn computing without having to use loops, variables, and object abstractions at the start. Requiring no prior programming experience, the book draws on Python's flexible data types and operations as well as its capacity for defining new functions. Along with the specifics of |
| from math import pi: Python for Engineers and Scientists Rakesh Nayak, Nishu Gupta, 2022-12-16 The text focuses on the basics of Python programming fundamentals and introduction to present-day applications in technology and the upcoming state-of-art trends in a comprehensive manner. The text is based on Python 3.x and it covers the fundamentals of Python with object-oriented concepts having numerous worked-out examples. It provides a learning tool for the students of beginner level as well as for researchers of advanced level. Each chapter contains additional examples that explain the usage of methods/functions discussed in the chapter. It provides numerous programming examples along with their outputs. The book • Includes programming tips to highlight the important concepts and help readers avoid common programming errors. • Provides programming examples along with their outputs to ensure the correctness and help readers in mastering the art of writing efficient Python programs. • Contains MCQ’s with their answers; conceptual questions and programming questions; and solutions to some selected programming questions, for every chapter. • Discusses applications like time zone converter and password generators at the end. • Covers fundamental of Python up to object oriented concepts including regular expression. The book offers a simple and lucid treatment of concepts supported with illustrations for easy understanding, provides numerous programming examples along with their outputs, and includes programming tips to highlight the important concepts. It will be a valuable resource for senior undergraduate, graduate students, and professionals in the fields of electrical engineering, electronics and communication engineering, and computer engineering. |
Math Study Resources - Answers
Math Delve into the study of matter, its properties, composition, structure, and the changes it undergoes during chemical reactions. Chemistry is the central science connecting other …
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Math and Arithmetic +2. What does slope measure? Asked by Anonymous. the rate of change in an object. Equation for slope is. Y2-Y1/X2-X1. A.K.A. The difference of the Y's over the …
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Nov 21, 2024 · Elephants have ivory tusks because ivory is a dense material that helps them maintain balance and stability. In a mathematical context, the joke may be a play on words, …
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Why did Pascal invent the first calculator in 1645? - Answers
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Nov 4, 2024 · What does 60 mean in the bible? Very little as far as i can see. In Lev.27.3, a man between the age of 20 & 60 is worth 50 shekels for a vow, and a woman, 30 shekels. - (a …
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Apr 20, 2025 · In the Caribbean Examinations Council (CXC) grading system, a Grade 1 is typically awarded for scores ranging from 75% to 100%. This grade indicates a high level of …
Math Study Resources - Answers
Math Delve into the study of matter, its properties, composition, structure, and the changes it undergoes during chemical reactions. Chemistry is the central science connecting other …
Study Resources - All Subjects - Answers
Math. Mathematics is an area of knowledge, which includes the study of such topics as numbers, formulas and related structures, shapes and spaces in which they are contained, and …
Answers - The Most Trusted Place for Answering Life's Questions
Math and Arithmetic +2. What does slope measure? Asked by Anonymous. the rate of change in an object. Equation for slope is. Y2-Y1/X2-X1. A.K.A. The difference of the Y's over the …
How long does it take to die from cutting a wrist? - Answers
Jan 24, 2025 · How long does it take to die after the wrist artery is cut? The time it takes to die after cutting the wrist artery can vary greatly depending on several factors, including the …
Why do elephant have ivory tusks math joke? - Answers
Nov 21, 2024 · Elephants have ivory tusks because ivory is a dense material that helps them maintain balance and stability. In a mathematical context, the joke may be a play on words, …
What day is the exact middle of the year? - Answers
Oct 2, 2024 · What day is halfway through the year? There are 365 days in a single year, so the middle of the year would be the 182.5 day of the year. July 1st is the 182nd day of the year …
Why did Pascal invent the first calculator in 1645? - Answers
Feb 6, 2025 · Continue Learning about Math & Arithmetic. What was the name of the second mechanical calculator invented in 1645 by Blaise Pascal? Pascaline. Is 1645 divisible by 5? …
All Topics - Answers
Geometry = Math of Euclid. Geometry is the Branch of math known for shapes (polygons), 3D figures, undefined terms, theorems, axioms, explanation of the universe, and pi. 330,616 …
What is 20 Shekels of Silver worth in Bible? - Answers
Nov 4, 2024 · What does 60 mean in the bible? Very little as far as i can see. In Lev.27.3, a man between the age of 20 & 60 is worth 50 shekels for a vow, and a woman, 30 shekels. - (a …
What percentage is considered a grade 1 in cxc? - Answers
Apr 20, 2025 · In the Caribbean Examinations Council (CXC) grading system, a Grade 1 is typically awarded for scores ranging from 75% to 100%. This grade indicates a high level of …
