Python Multimedia PDF Download
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Author: Ninad Sathaye
Publisher: Packt Publishing Ltd
ISBN: 1849510172
Category : Computers
Languages : en
Pages : 441
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Book Description
A practical guide, this book provides step-by-step instructions for developing multimedia applications, showcasing real world examples throughout. This book is for Python developers who want to dip their toes into working with images, animations, audio and video processing using Python.
Author: Ninad Sathaye
Publisher: Packt Publishing Ltd
ISBN: 1849510172
Category : Computers
Languages : en
Pages : 441
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Book Description
A practical guide, this book provides step-by-step instructions for developing multimedia applications, showcasing real world examples throughout. This book is for Python developers who want to dip their toes into working with images, animations, audio and video processing using Python.
Author: Louise Spilsbury
Publisher: Capstone Classroom
ISBN: 9781403473684
Category : Juvenile Nonfiction
Languages : en
Pages : 36
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Book Description
This book introduces plants, where they live, and how they grow and reproduce.
Author: Mark J. Guzdial
Publisher: Prentice Hall
ISBN: 9780133591521
Category : Computers
Languages : en
Pages : 448
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Book Description
Introduction to Computing and Programming in Python, 3e, uses multimedia applications to motivate introductory computer science majors or non-majors. The book's hands-on approach shows how programs can be used to build multimedia computer science applications that include sound, graphics, music, pictures, and movies. The students learn a key set of computer science tools and topics, as well as programming skills; such as how to design and use algorithms, and practical software engineering methods. The book also includes optional coverage of HCI, as well as rudimentary data structures and databases using the user-friendly Python language for implementation. Authors Guzdial and Ericson also demonstrate how to communicate compatibly through networks and do concurrent programming. 0133591522 / 9780133591521 Introduction to Computing and Programming in Python & MyProgrammingLab with eText Package Package consists of 0132923513 / 9780132923514 Introduction to Computing and Programming in Python 0133590747 / 9780133590746 MyProgrammingLab with eText -- Access Code Card -- for Introduction to Computing and Programming in Python
Author: Marco Bonzanini
Publisher: Packt Publishing Ltd
ISBN: 1783552026
Category : Computers
Languages : en
Pages : 333
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Book Description
Acquire and analyze data from all corners of the social web with Python About This Book Make sense of highly unstructured social media data with the help of the insightful use cases provided in this guide Use this easy-to-follow, step-by-step guide to apply analytics to complicated and messy social data This is your one-stop solution to fetching, storing, analyzing, and visualizing social media data Who This Book Is For This book is for intermediate Python developers who want to engage with the use of public APIs to collect data from social media platforms and perform statistical analysis in order to produce useful insights from data. The book assumes a basic understanding of the Python Standard Library and provides practical examples to guide you toward the creation of your data analysis project based on social data. What You Will Learn Interact with a social media platform via their public API with Python Store social data in a convenient format for data analysis Slice and dice social data using Python tools for data science Apply text analytics techniques to understand what people are talking about on social media Apply advanced statistical and analytical techniques to produce useful insights from data Build beautiful visualizations with web technologies to explore data and present data products In Detail Your social media is filled with a wealth of hidden data – unlock it with the power of Python. Transform your understanding of your clients and customers when you use Python to solve the problems of understanding consumer behavior and turning raw data into actionable customer insights. This book will help you acquire and analyze data from leading social media sites. It will show you how to employ scientific Python tools to mine popular social websites such as Facebook, Twitter, Quora, and more. Explore the Python libraries used for social media mining, and get the tips, tricks, and insider insight you need to make the most of them. Discover how to develop data mining tools that use a social media API, and how to create your own data analysis projects using Python for clear insight from your social data. Style and approach This practical, hands-on guide will help you learn everything you need to perform data mining for social media. Throughout the book, we take an example-oriented approach to use Python for data analysis and provide useful tips and tricks that you can use in day-to-day tasks.
Author: Barbara Ericson
Publisher: Prentice Hall
ISBN: 0136060277
Category :
Languages : en
Pages : 433
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Book Description
Author: Jonathan Borwein
Publisher: Springer Science & Business Media
ISBN: 364256240X
Category : Computers
Languages : en
Pages : 312
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Book Description
This book on multimedia tools for communicating mathematics arose from presentations at an international workshop organized by the Centro de Matemtica e Aplicacoes Fundamentais at the University of Lisbon, in November 2000, with the collaboration of the Sonderforschungsbereich 288 at the University of Technology in Berlin, and of the Centre for Experimental and Constructive Mathematics at Simon Fraser University in Burnaby, Canada. The MTCM2000 meeting aimed at the scientific methods and algorithms at work inside multimedia tools, and it provided an overview of the range of present multimedia projects, of their limitations and the underlying mathematical problems. This book presents some of the tools and algorithms currently being used to create new ways of making enhanced interactive presentations and multimedia courses. It is an invaluable and up-to-date reference book on multimedia tools presently available for mathematics and related subjects.
Author: Siddhartha Chatterjee
Publisher: Packt Publishing Ltd
ISBN: 1787126757
Category : Computers
Languages : en
Pages : 307
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Book Description
Leverage the power of Python to collect, process, and mine deep insights from social media data About This Book Acquire data from various social media platforms such as Facebook, Twitter, YouTube, GitHub, and more Analyze and extract actionable insights from your social data using various Python tools A highly practical guide to conducting efficient social media analytics at scale Who This Book Is For If you are a programmer or a data analyst familiar with the Python programming language and want to perform analyses of your social data to acquire valuable business insights, this book is for you. The book does not assume any prior knowledge of any data analysis tool or process. What You Will Learn Understand the basics of social media mining Use PyMongo to clean, store, and access data in MongoDB Understand user reactions and emotion detection on Facebook Perform Twitter sentiment analysis and entity recognition using Python Analyze video and campaign performance on YouTube Mine popular trends on GitHub and predict the next big technology Extract conversational topics on public internet forums Analyze user interests on Pinterest Perform large-scale social media analytics on the cloud In Detail Social Media platforms such as Facebook, Twitter, Forums, Pinterest, and YouTube have become part of everyday life in a big way. However, these complex and noisy data streams pose a potent challenge to everyone when it comes to harnessing them properly and benefiting from them. This book will introduce you to the concept of social media analytics, and how you can leverage its capabilities to empower your business. Right from acquiring data from various social networking sources such as Twitter, Facebook, YouTube, Pinterest, and social forums, you will see how to clean data and make it ready for analytical operations using various Python APIs. This book explains how to structure the clean data obtained and store in MongoDB using PyMongo. You will also perform web scraping and visualize data using Scrappy and Beautifulsoup. Finally, you will be introduced to different techniques to perform analytics at scale for your social data on the cloud, using Python and Spark. By the end of this book, you will be able to utilize the power of Python to gain valuable insights from social media data and use them to enhance your business processes. Style and approach This book follows a step-by-step approach to teach readers the concepts of social media analytics using the Python programming language. To explain various data analysis processes, real-world datasets are used wherever required.
Author: Wes McKinney
Publisher: "O'Reilly Media, Inc."
ISBN: 1491957611
Category : Computers
Languages : en
Pages : 553
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Book Description
Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples
Author: Phillip D. Brooker
Publisher: SAGE
ISBN: 1526486342
Category : Social Science
Languages : en
Pages : 370
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Book Description
As data become ′big′, fast and complex, the software and computing tools needed to manage and analyse them are rapidly developing. Social scientists need new tools to meet these challenges, tackle big datasets, while also developing a more nuanced understanding of - and control over - how these computing tools and algorithms are implemented. Programming with Python for Social Scientists offers a vital foundation to one of the most popular programming tools in computer science, specifically for social science researchers, assuming no prior coding knowledge. It guides you through the full research process, from question to publication, including: the fundamentals of why and how to do your own programming in social scientific research, questions of ethics and research design, a clear, easy to follow ′how-to′ guide to using Python, with a wide array of applications such as data visualisation, social media data research, social network analysis, and more. Accompanied by numerous code examples, screenshots, sample data sources, this is the textbook for social scientists looking for a complete introduction to programming with Python and incorporating it into their research design and analysis.
Author: Jake VanderPlas
Publisher: "O'Reilly Media, Inc."
ISBN: 1491912138
Category : Computers
Languages : en
Pages : 609
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Book Description
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
