Download or read book Python Annotated Archives written by Martin C. Brown and published by Osborne Publishing. This book was released on 2000 with total page 760 pages. Available in PDF, EPUB and Kindle. Book excerpt: Expert annotations show when and how to customize Python code examples to fit individual development needs. Brown covers data manipulation, networking, Web and interface development, graphics, e-mail and more. The bonus CD-ROM contains all code from the book, saving readers hundreds of programming hours.
Download or read book JavaScript Annotated Archives written by Jeff Frentzen and published by . This book was released on 1998 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: Like no other book before, "JavaScript Annotated Archives" gives you the best in expert advice on how, when and why you should implement examples from a powerful collection of ready-to-use code into your Web pages. These helpful annotations are provided by three JavaScript programming experts, including PC Week's "Jeff's Internet Adventures" columnist, Jeff Frentzen. They'll teach you numerous customization tips and techniques that can be applied to the book's JavaScript code examples for use in your own projects. Included with the book is a useful CD-ROM containing all the book's source code as well as Web pages that demonstrate each script. Add these Web pages immediately to your site or customize them using the expert annotations.
Download or read book Python for Data Analysis written by Wes McKinney and published by "O'Reilly Media, Inc.". This book was released on 2017-09-25 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Core Python Programming written by Wesley Chun and published by Prentice Hall Professional. This book was released on 2001 with total page 805 pages. Available in PDF, EPUB and Kindle. Book excerpt: Experts and novices alike will be able to find information about every command they'll need to use Linux. This complete, practical desk reference is organized by function, with a road map-style alphabetical reference for quick access of information about all aspects of running and administering the program. The CD-ROM contains Windows and Linux Python distributions plus extensive cross-platform source code from the book.
Download or read book Python Data Science Handbook written by Jake VanderPlas and published by "O'Reilly Media, Inc.". This book was released on 2016-11-21 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Annotated Algorithms in Python written by Massimo Di Pierro and published by Experts4solutions. This book was released on 2013-11 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is assembled from lectures given by the author over a period of 10 years at the School of Computing of DePaul University. The lectures cover multiple classes, including Analysis and Design of Algorithms, Scientific Computing, Monte Carlo Simulations, and Parallel Algorithms. These lectures teach the core knowledge required by any scientist interested in numerical algorithms and by students interested in computational finance.
Download or read book Python in a Nutshell written by Alex Martelli and published by "O'Reilly Media, Inc.". This book was released on 2023-01-09 with total page 757 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python was recently ranked as today's most popular programming language on the TIOBE index, thanks to its broad applicability to design and prototyping to testing, deployment, and maintenance. With this updated fourth edition, you'll learn how to get the most out of Python, whether you're a professional programmer or someone who needs this language to solve problems in a particular field. Carefully curated by recognized experts in Python, this new edition focuses on version 3.10, bringing this seminal work on the Python language fully up to date on five version releases, including preview coverage of upcoming 3.11 features. This handy guide will help you: Learn how Python represents data and program as objects Understand the value and uses of type annotations Examine which language features appeared in which recent versions Discover how to use modern Python idiomatically Learn ways to structure Python projects appropriately Understand how to debug Python code
Download or read book Text Analytics with Python written by Dipanjan Sarkar and published by Apress. This book was released on 2019-05-21 with total page 688 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage Natural Language Processing (NLP) in Python and learn how to set up your own robust environment for performing text analytics. This second edition has gone through a major revamp and introduces several significant changes and new topics based on the recent trends in NLP. You’ll see how to use the latest state-of-the-art frameworks in NLP, coupled with machine learning and deep learning models for supervised sentiment analysis powered by Python to solve actual case studies. Start by reviewing Python for NLP fundamentals on strings and text data and move on to engineering representation methods for text data, including both traditional statistical models and newer deep learning-based embedding models. Improved techniques and new methods around parsing and processing text are discussed as well. Text summarization and topic models have been overhauled so the book showcases how to build, tune, and interpret topic models in the context of an interest dataset on NIPS conference papers. Additionally, the book covers text similarity techniques with a real-world example of movie recommenders, along with sentiment analysis using supervised and unsupervised techniques. There is also a chapter dedicated to semantic analysis where you’ll see how to build your own named entity recognition (NER) system from scratch. While the overall structure of the book remains the same, the entire code base, modules, and chapters has been updated to the latest Python 3.x release. What You'll Learn • Understand NLP and text syntax, semantics and structure• Discover text cleaning and feature engineering• Review text classification and text clustering • Assess text summarization and topic models• Study deep learning for NLP Who This Book Is For IT professionals, data analysts, developers, linguistic experts, data scientists and engineers and basically anyone with a keen interest in linguistics, analytics and generating insights from textual data.
Download or read book Coreference written by Maciej Ogrodniczuk and published by Walter de Gruyter GmbH & Co KG. This book was released on 2014-12-12 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: ‘Coreference’ presents specificities of reference, anaphora and coreference in Polish, establish identity-of-reference annotation model and present methodology used to create the corpus of Polish general nominal coreference. Various resolution approaches are presented, followed by their evaluation. By discussing the subsequent steps of building a coreference-related component of the natural language processing toolset and offering deeper explanation of the decisions taken, this volume might also serve as a reference book on state-of the art methods of carrying out coreference projects for new languages and a tutorial for NLP practitioners. Apart from serving as a description of the fi rst complete approach to annotation and resolution of direct nominal coreference for Polish, this book is a useful starting point for further work on other types of anaphora/coreference, semantic annotation, cognitive linguistics (related to the topic of near-identity, discussed in the book) etc. With extended tutorial-like sections on important subtopics, such as evaluation metrics for coreference resolution, it can prove useful to both researchers and practitioners interested in semantic description of Balto-Slavic languages and their processing, engineers developing language resources, tools and linguistic processing chains, as well as computational linguists in general.
Download or read book Python Standard Library written by Fredrik Lundh and published by "O'Reilly Media, Inc.". This book was released on 2001 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: CD-ROM contains: programming examples from the book and a demo of the PythonWorks IDE.
Download or read book Provenance and Annotation of Data and Processes written by Juliana Freire and published by Springer. This book was released on 2008-11-19 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the Second International Provenance and Annotation Workshop, IPAW 2008, held in Salt Lake City, UT, USA, in June 2007. The 14 revised full papers and 15 revised short and demo papers presented together with 2 keynote lectures were carefully reviewed and selected from 40 submissions. The paper are organized in topical sections on provenance: models and querying; provenance: visualization, failures, identity; provenance and workflows; provenance for streams and collaboration; and applications.
Download or read book Learn Data Analysis with Python written by A.J. Henley and published by Apress. This book was released on 2018-02-22 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get started using Python in data analysis with this compact practical guide. This book includes three exercises and a case study on getting data in and out of Python code in the right format. Learn Data Analysis with Python also helps you discover meaning in the data using analysis and shows you how to visualize it. Each lesson is, as much as possible, self-contained to allow you to dip in and out of the examples as your needs dictate. If you are already using Python for data analysis, you will find a number of things that you wish you knew how to do in Python. You can then take these techniques and apply them directly to your own projects. If you aren’t using Python for data analysis, this book takes you through the basics at the beginning to give you a solid foundation in the topic. As you work your way through the book you will have a better of idea of how to use Python for data analysis when you are finished. What You Will Learn Get data into and out of Python code Prepare the data and its format Find the meaning of the data Visualize the data using iPython Who This Book Is For Those who want to learn data analysis using Python. Some experience with Python is recommended but not required, as is some prior experience with data analysis or data science.
Download or read book Provenance and Annotation of Data and Process written by Deborah L. McGuinness and published by Springer Science & Business Media. This book was released on 2011-01-04 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 7 revised full papers, 11 revised medium-length papers, 6 revised short, and 7 demo papers presented together with 10 poster/abstract papers describing late-breaking work were carefully reviewed and selected from numerous submissions. Provenance has been recognized to be important in a wide range of areas including databases, workflows, knowledge representation and reasoning, and digital libraries. Thus, many disciplines have proposed a wide range of provenance models, techniques, and infrastructure for encoding and using provenance. The papers investigate many facets of data provenance, process documentation, data derivation, and data annotation.
Download or read book The Complete Idiot s Guide to Solaris 9 written by Martin C. Brown and published by Penguin. This book was released on 2002 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: A primer written to teach the fundamentals of setting up and maintining a network within the Solaris operating environment.
Download or read book Genre Analysis and Corpus Design written by Ulrike Henny-Krahmer and published by BoD – Books on Demand. This book was released on 2024-01-22 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work in the field of digital literary stylistics and computational literary studies is concerned with theoretical concerns of literary genre, with the design of a corpus of nineteenth-century Spanish-American novels, and with its empirical analysis in terms of subgenres of the novel. The digital text corpus consists of 256 Argentine, Cuban, and Mexican novels from the period between 1830 and 1910. It has been created with the goal to analyze thematic subgenres and literary currents that were represented in numerous novels in the nineteenth century by means of computational text categorization methods. To categorize the texts, statistical classification and a family resemblance analysis relying on network analysis are used with the aim to examine how the subgenres, which are understood as communicative, conventional phenomena, can be captured on the stylistic, textual level of the novels that participate in them.
Download or read book Dr Dobb s Journal written by and published by . This book was released on 2000-07 with total page 1080 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Provenance and Annotation of Data and Processes written by Boris Glavic and published by Springer Nature. This book was released on 2021-07-08 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 8th and 9th International Provenance and Annotation Workshop, IPAW 2020 and IPAW 2021 which were held as part of ProvenanceWeek in 2020 and 2021. Due to the COVID-19 pandemic, PropvenanceWeek 2020 was held as a 1-day virtual event with brief teaser talks on June 22, 2020. In 2021, the conference was held virtually during July 19-22, 2021. The 11 full papers and 12 posters and system demonstrations included in these proceedings were carefully reviewed and selected from a total of 31 submissions. They were organized in the following topical sections: provenance capture and representation; security; provenance types, inference, queries and summarization; reliability and trustworthiness; joint IPAW/TaPP poster and demonstration session.