Learning Scientific Programming With Python
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Learning Scientific Programming With Python
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Author : Christian Hill
language : en
Publisher: Cambridge University Press
Release Date : 2015
Learning Scientific Programming With Python written by Christian Hill and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Computers categories.
Learn to master basic programming tasks from scratch with real-life scientific examples in this complete introduction to Python.
Introduction To Scientific Programming With Python
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Author : Pankaj Jayaraman
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Introduction To Scientific Programming With Python written by Pankaj Jayaraman and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Computers categories.
"Introduction to Scientific Programming with Python" offers an immersive exploration into the dynamic field of scientific programming using Python. We cater to a diverse audience, serving as an entry point for novices and a valuable resource for seasoned practitioners in scientific computing. Python's popularity in scientific circles stems from its readability, versatility, and extensive libraries for numerical computing, data analysis, and visualization. We cover fundamental programming concepts and gradually introduce advanced techniques specific to scientific applications. From mastering Python basics to exploring advanced topics like machine learning and symbolic mathematics, each chapter provides a structured and hands-on learning experience. Real-world case studies, practical examples, and exercises ensure readers grasp theoretical concepts and gain practical skills. Throughout the book, Python becomes a tool of empowerment, enabling readers to unravel complex scientific data, model intricate phenomena, and contribute meaningfully to their fields. "Introduction to Scientific Programming with Python" is an invaluable companion for harnessing Python's potential in scientific inquiry and discovery. By the end, readers will have a robust foundation in Python and the confidence to apply scientific programming methodologies to real-world problems. This book unlocks the door to a world where Python drives exploration, discovery, and innovation in science.
A Primer On Scientific Programming With Python
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Author : Hans Petter Langtangen
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-03-31
A Primer On Scientific Programming With Python written by Hans Petter Langtangen 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 2011-03-31 with Computers categories.
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.
Cern Courier
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Author :
language : en
Publisher:
Release Date : 2016
Cern Courier written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Nuclear energy categories.
Introduction To Scientific Programming With Python
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Author : Joakim Sundnes
language : en
Publisher: Springer Nature
Release Date : 2020-07-01
Introduction To Scientific Programming With Python written by Joakim Sundnes and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-01 with Mathematics categories.
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.
Applied Scientific Computing
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Author : Peter R. Turner
language : en
Publisher: Springer
Release Date : 2018-07-18
Applied Scientific Computing written by Peter R. Turner and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-18 with Computers categories.
This easy-to-understand textbook presents a modern approach to learning numerical methods (or scientific computing), with a unique focus on the modeling and applications of the mathematical content. Emphasis is placed on the need for, and methods of, scientific computing for a range of different types of problems, supplying the evidence and justification to motivate the reader. Practical guidance on coding the methods is also provided, through simple-to-follow examples using Python. Topics and features: provides an accessible and applications-oriented approach, supported by working Python code for many of the methods; encourages both problem- and project-based learning through extensive examples, exercises, and projects drawn from practical applications; introduces the main concepts in modeling, python programming, number representation, and errors; explains the essential details of numerical calculus, linear, and nonlinear equations, including the multivariable Newton method; discusses interpolation and the numerical solution of differential equations, covering polynomial interpolation, splines, and the Euler, Runge–Kutta, and shooting methods; presents largely self-contained chapters, arranged in a logical order suitable for an introductory course on scientific computing. Undergraduate students embarking on a first course on numerical methods or scientific computing will find this textbook to be an invaluable guide to the field, and to the application of these methods across such varied disciplines as computer science, engineering, mathematics, economics, the physical sciences, and social science.
Python For Programmers
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Author : Paul Deitel
language : en
Publisher: Prentice Hall
Release Date : 2019-03-15
Python For Programmers written by Paul Deitel and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-15 with Computers categories.
The professional programmer’s Deitel® guide to Python® with introductory artificial intelligence case studies Written for programmers with a background in another high-level language, Python for Programmers uses hands-on instruction to teach today’s most compelling, leading-edge computing technologies and programming in Python–one of the world’s most popular and fastest-growing languages. Please read the Table of Contents diagram inside the front cover and the Preface for more details. In the context of 500+, real-world examples ranging from individual snippets to 40 large scripts and full implementation case studies, you’ll use the interactive IPython interpreter with code in Jupyter Notebooks to quickly master the latest Python coding idioms. After covering Python Chapters 1-5 and a few key parts of Chapters 6-7, you’ll be able to handle significant portions of the hands-on introductory AI case studies in Chapters 11-16, which are loaded with cool, powerful, contemporary examples. These include natural language processing, data mining Twitter® for sentiment analysis, cognitive computing with IBM® WatsonTM, supervised machine learning with classification and regression, unsupervised machine learning with clustering, computer vision through deep learning and convolutional neural networks, deep learning with recurrent neural networks, big data with Hadoop®, SparkTM and NoSQL databases, the Internet of Things and more. You’ll also work directly or indirectly with cloud-based services, including Twitter, Google TranslateTM, IBM Watson, Microsoft® Azure®, OpenMapQuest, PubNub and more. Features 500+ hands-on, real-world, live-code examples from snippets to case studies IPython + code in Jupyter® Notebooks Library-focused: Uses Python Standard Library and data science libraries to accomplish significant tasks with minimal code Rich Python coverage: Control statements, functions, strings, files, JSON serialization, CSV, exceptions Procedural, functional-style and object-oriented programming Collections: Lists, tuples, dictionaries, sets, NumPy arrays, pandas Series & DataFrames Static, dynamic and interactive visualizations Data experiences with real-world datasets and data sources Intro to Data Science sections: AI, basic stats, simulation, animation, random variables, data wrangling, regression AI, big data and cloud data science case studies: NLP, data mining Twitter®, IBM® WatsonTM, machine learning, deep learning, computer vision, Hadoop®, SparkTM, NoSQL, IoT Open-source libraries: NumPy, pandas, Matplotlib, Seaborn, Folium, SciPy, NLTK, TextBlob, spaCy, Textatistic, Tweepy, scikit-learn®, Keras and more Accompanying code examples are available here: http://ptgmedia.pearsoncmg.com/imprint_downloads/informit/bookreg/9780135224335/9780135224335_examples.zip. Register your product for convenient access to downloads, updates, and/or corrections as they become available. See inside book for more information.
Python Programming Basic To Advanced
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Author : Puja S. Gholap
language : en
Publisher: GRIN Verlag
Release Date : 2025-05-26
Python Programming Basic To Advanced written by Puja S. Gholap and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-26 with Computers categories.
Document from the year 2025 in the subject Engineering - Computer Engineering, grade: A, Savitribai Phule Pune University, formerly University of Pune (Savitribai Phule Pune University), course: B.E, language: English, abstract: Welcome to a comprehensive journey through the world of Python programming, a language that has revolutionized the field of computer science and continues to be a vital tool in various professional domains. This book, "Python Programming for All: Basic to Advanced," aims to empower readers like you with the knowledge and skills to harness the full potential of Python, no matter your starting point. Python's simplicity and versatility have made it one of the most beloved programming languages among both beginners and seasoned coders. Whether you are a student, a hobbyist, a professional coder, or even someone from a non-technical background looking to dip your toes into the world of programming, this book is for you. The book is structured to provide a gradual learning experience, starting from the very basics and gradually moving towards advanced concepts. In the early chapters, you will be introduced to the fundamental aspects of Python, such as syntax, data types, and control structures. As you progress, you will explore more complex topics like object-oriented programming, data structures, algorithms, and more. By the end, you will be equipped to use Python for a wide range of applications, from web development and data analysis to artificial intelligence and machine learning. Each chapter is designed with a balance of theory and practical examples, followed by exercises that reinforce learning. The book also includes useful tips and tricks, common pitfalls to avoid, and insights into how Python is used in the real world. The goal of "Python Programming for All: Basic to Advance" is not just to teach you Python, but also to instill a problem-solving mindset and coding best practices. This will enable you to not just understand Python, but also to think like a Python programmer. We hope that this book will ignite your passion for programming and open up new opportunities for you in the digital world. So, get ready to embark on a thrilling adventure into the world of Python programming!
Python Machine Learning
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Author : Wei-Meng Lee
language : en
Publisher: John Wiley & Sons
Release Date : 2019-04-30
Python Machine Learning written by Wei-Meng Lee and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-30 with Computers categories.
Python makes machine learning easy for beginners and experienced developers With computing power increasing exponentially and costs decreasing at the same time, there is no better time to learn machine learning using Python. Machine learning tasks that once required enormous processing power are now possible on desktop machines. However, machine learning is not for the faint of heart—it requires a good foundation in statistics, as well as programming knowledge. Python Machine Learning will help coders of all levels master one of the most in-demand programming skillsets in use today. Readers will get started by following fundamental topics such as an introduction to Machine Learning and Data Science. For each learning algorithm, readers will use a real-life scenario to show how Python is used to solve the problem at hand. Python data science—manipulating data and data visualization Data cleansing Understanding Machine learning algorithms Supervised learning algorithms Unsupervised learning algorithms Deploying machine learning models Python Machine Learning is essential reading for students, developers, or anyone with a keen interest in taking their coding skills to the next level.
Python For Data Science
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Author : Daniel O'Reilly
language : en
Publisher:
Release Date : 2021-02-08
Python For Data Science written by Daniel O'Reilly and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-08 with Computers categories.
★55% OFF for bookstores! NOW at $35.95 instead of $45.95!★ Would you like to: ● Learn a super competitive skill? ● Become irreplaceable in the future job market? ● Upgrade yourself to the ultimate data whizz? Here's the Perfect Solution if Your Customers Want to Become the Master of Data Science and Learn Phyton Step-by-Step Data science is one of the emerging technologies that is set to radically transform the job market. With applications in almost every industry, data science experts will have no shortage of great job offers. But, the whole field may seem a little intimidating if your background is not specific to data science. This book is here to guide you through the field of data science from the very beginning. You will learn the fundamental skills and tools to support your learning process. If you're a beginner, this is the book to help you easily understand the basics of data science. To understand data science, you also need a good understanding of how Python helps you design and implement these projects. This guidebook is going to explain how we can get all of this done. Here just a little preview of what you'll find inside this book: ● A thorough and simple explanation of data science and the way it works ● Basics of data science and fundamental skills you need to get started ● Data science libraries you need to learn to become a data whizz ● A blueprint for the most used frameworks for Python data science ● How to process and understand the data and design your own projects AND SO MUCH MORE! Even if you're an absolute beginner with little programming experience, you will find this book easy to follow and implement. This guide is your first step towards a successful data science career, so don't hesitate!