Langtangen, Hans Petter, Python Scripting for Computational Science, Springer, 2008. , A Primer on Scientific Programming with Python, 3rd ed., Springer, Berlin, 2012. Liang, Y. Daniel, Introduction to Programming Using Python, ...
Author: M. N. RAO
Publisher: PHI Learning Pvt. Ltd.
Free Open Source Software have been growing enormously in the field of information technology. Open Source Software (OSS) is a software whose source code is accessible for alteration or enrichment by other programmers. This book gives a detailed analysis of open source software and their fundamentals, and so is meant for the beginners who want to learn and write programs using Open Source Software. It also educates on how to download and instal these open source free software in the system.The topics covered in the book broadly aims to develop familiar Open Source Software (OSS) associated with database, web portal and scientific application development. Software platforms like, Android, MySQL, PHP, Python, PERL, Grid Computing, and Open Source Cloud, and their applications are explained through various examples and programs. The platforms like OSS and Linux are also introduced in the book. Recapitulation given at the end of each chapter enables the readers to take a quick revision of the topics. Numerous examples in the form of programs are given to enable the students to understand the theoretical concepts and their applicative knowledge. The book is an introductory textbook on Open Source Software (OSS) for the undergraduate students of Computer Science Engineering (CSE) and postgraduate students of Computer Application (MCA). Salient Features The procedure for installing software (Linux, Android, PHP, MySQL, Perl, and Python) both in Linux and Windows operating systems are discussed in the book.• Numerous worked out example programs are introduced.• Inclusion of several questions drawn from previous question papers in chapter-end exercises.
- Tariq Rashid hat eine besondere Fähigkeit, schwierige Konzepte verständlich zu erklären, dadurch werden Neuronale Netze für jeden Interessierten zugänglich und praktisch nachvollziehbar.
Author: Tariq Rashid
Neuronale Netze sind Schlüsselelemente des Deep Learning und der Künstlichen Intelligenz, die heute zu Erstaunlichem in der Lage sind. Dennoch verstehen nur wenige, wie Neuronale Netze tatsächlich funktionieren. Dieses Buch nimmt Sie mit auf eine unterhaltsame Reise, die mit ganz einfachen Ideen beginnt und Ihnen Schritt für Schritt zeigt, wie Neuronale Netze arbeiten. Dafür brauchen Sie keine tieferen Mathematik-Kenntnisse, denn alle mathematischen Konzepte werden behutsam und mit vielen Illustrationen erläutert. Dann geht es in die Praxis: Sie programmieren Ihr eigenes Neuronales Netz mit Python und bringen ihm bei, handgeschriebene Zahlen zu erkennen, bis es eine Performance wie ein professionell entwickeltes Netz erreicht. Zum Schluss lassen Sie das Netz noch auf einem Raspberry Pi Zero laufen. - Tariq Rashid hat eine besondere Fähigkeit, schwierige Konzepte verständlich zu erklären, dadurch werden Neuronale Netze für jeden Interessierten zugänglich und praktisch nachvollziehbar.
Practical Programming: An Introduction to Computer Science Using Python. Raleigh, NC: The Pragmatic Bookshelf, 2009. Dawson, Michael. Python Programming for the Absolute Beginner. 3rd ed. Boston, MA: Course Technology, 2010.
Author: Simone Payment
Publisher: The Rosen Publishing Group, Inc
Category: Juvenile Nonfiction
Beginner coders often gravitate to the easy-to-use Python language for its versatility and usability. Games, robots, and Web sites—including those of Google and YouTube—and much more run on Python, and developers are constantly collaborating to improve the language and address problem areas. This volume introduces readers to Python, exploring its various applications and the history of its development. Side-by-side comparisons with other languages are also included to show the benefits of Python, while interviews with programmers highlight its many real-world applications.
Computer science taught with Python: Python Programming: An Introduction to Computer Science, 3rd Edition by John Zelle (author) Python machine learning and analytics: Python Machine Learning: Machine Learning and Deep Learning with ...
Author: Nathan Greeneltch
Publisher: Packt Publishing Ltd
Explore the different data mining techniques using the libraries and packages offered by Python Key Features Grasp the basics of data loading, cleaning, analysis, and visualization Use the popular Python libraries such as NumPy, pandas, matplotlib, and scikit-learn for data mining Your one-stop guide to build efficient data mining pipelines without going into too much theory Book Description Data mining is a necessary and predictable response to the dawn of the information age. It is typically defined as the pattern and/ or trend discovery phase in the data mining pipeline, and Python is a popular tool for performing these tasks as it offers a wide variety of tools for data mining. This book will serve as a quick introduction to the concept of data mining and putting it to practical use with the help of popular Python packages and libraries. You will get a hands-on demonstration of working with different real-world datasets and extracting useful insights from them using popular Python libraries such as NumPy, pandas, scikit-learn, and matplotlib. You will then learn the different stages of data mining such as data loading, cleaning, analysis, and visualization. You will also get a full conceptual description of popular data transformation, clustering, and classification techniques. By the end of this book, you will be able to build an efficient data mining pipeline using Python without any hassle. What you will learn Explore the methods for summarizing datasets and visualizing/plotting data Collect and format data for analytical work Assign data points into groups and visualize clustering patterns Learn how to predict continuous and categorical outputs for data Clean, filter noise from, and reduce the dimensions of data Serialize a data processing model using scikit-learn’s pipeline feature Deploy the data processing model using Python’s pickle module Who this book is for Python developers interested in getting started with data mining will love this book. Budding data scientists and data analysts looking to quickly get to grips with practical data mining with Python will also find this book to be useful. Knowledge of Python programming is all you need to get started.
3rd ed. Sebastapol, Calif.: O'Reilly, 2006. Python Programming Language—Official Web site. Available online. URL: http://www.python.org/. Accessed August 17, 2007. Zelle, John m. Python Programming: An Introduction to Computer Science.
Author: Harry Henderson
Publisher: Infobase Publishing
Category: Computer science
Presents an illustrated A-Z encyclopedia containing approximately 600 entries on computer and technology related topics.
Some good introductory Python resources include Lutz, M. 2007. Learning Python, 3rd edition. O'Reilly & Associates, Inc., Sebastopol, CA. Zelle, J. M. 2003.Python Programming: An Introduction to Computer Science.
Author: Rob O'Neill
Publisher: CRC Press
Digital characters are a driving force in the entertainment industry today. Every animated film and video game production spends a large percentage of its resources and time on advancing the quality of the digital characters inhabiting the world being created. This book presents the theory and practice behind the creation of digital characters for
This book will help you explore the foundations of Python programming and learn how Python can be used to achieve results.
Author: Fabrizio Romano
Get up and running with Python through concise tutorials and practical projects in this fully updated edition Key Features: Discover how to think like a Python programmer Extensively revised with richer examples, Python 3.9 syntax, and new chapters on APIs and packaging and distributing Python code Learn the fundamentals of Python through real-world projects in API development, GUI programming, and data science Book Description: Learn Python Programming, Third Edition is both a theoretical and practical introduction to Python, an extremely flexible and powerful programming language that can be applied to many disciplines. This book will make learning Python easy and give you a thorough understanding of the language. You'll learn how to write programs, build modern APIs, and work with data by using renowned Python data science libraries. This revised edition covers the latest updates on API management, packaging applications, and testing. There is also broader coverage of context managers and an updated data science chapter. The book empowers you to take ownership of writing your software and become independent in fetching the resources you need. You will have a clear idea of where to go and how to build on what you have learned from the book. Through examples, the book explores a wide range of applications and concludes by building real-world Python projects based on the concepts you have learned. What You Will Learn: Get Python up and running on Windows, Mac, and Linux Write elegant, reusable, and efficient code in any situation Avoid common pitfalls like duplication, complicated design, and over-engineering Understand when to use the functional or object-oriented approach to programming Build a simple API with FastAPI and program GUI applications with Tkinter Get an initial overview of more complex topics such as data persistence and cryptography Fetch, clean, and manipulate data, making efficient use of Python's built-in data structures Who this book is for: This book is for anyone who has some programming experience, but not necessarily with Python. Some knowledge of basic programming concepts will come in handy, although it is not a requirement.
Write programs to solve real-world problems, and come away with everything you need to produce quality code. This edition has been updated to use the new language features in Python 3.6.
Author: Paul Gries
Publisher: Pragmatic Bookshelf
Classroom-tested by tens of thousands of students, this new edition of the bestselling intro to programming book is for anyone who wants to understand computer science. Learn about design, algorithms, testing, and debugging. Discover the fundamentals of programming with Python 3.6--a language that's used in millions of devices. Write programs to solve real-world problems, and come away with everything you need to produce quality code. This edition has been updated to use the new language features in Python 3.6.
Next add the response “6” to the list between the values 7 and 3 (in what will be the third position in the list) using the.insert() method. ... Python programming: An introduction to computer science (2nd ed.).
Author: Frederick Kaefer
Publisher: SAGE Publications
Category: Business & Economics
Would you like to gather big datasets, analyze them, and visualize the results, all in one program? If this describes you, then Introduction to Python Programming for Business and Social Science Applications is the book for you. Authors Frederick Kaefer and Paul Kaefer walk you through each step of the Python package installation and analysis process, with frequent exercises throughout so you can immediately try out the functions you’ve learned. Written in straightforward language for those with no programming background, this book will teach you how to use Python for your research and data analysis. Instead of teaching you the principles and practices of programming as a whole, this application-oriented text focuses on only what you need to know to research and answer social science questions. The text features two types of examples, one set from the General Social Survey and one set from a large taxi trip dataset from a major metropolitan area, to help readers understand the possibilities of working with Python. Chapters on installing and working within a programming environment, basic skills, and necessary commands will get you up and running quickly, while chapters on programming logic, data input and output, and data frames help you establish the basic framework for conducting analyses. Further chapters on web scraping, statistical analysis, machine learning, and data visualization help you apply your skills to your research. More advanced information on developing graphical user interfaces (GUIs) help you create functional data products using Python to inform general users of data who don’t work within Python. First there was IBM® SPSS®, then there was R, and now there′s Python. Statistical software is getting more aggressive - let authors Frederick Kaefer and Paul Kaefer help you tame it with Introduction to Python Programming for Business and Social Science Applications.