Data Munging With Perl
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Data Munging With Perl
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Author : David Cross
language : en
Publisher:
Release Date : 2001
Data Munging With Perl written by David Cross and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Data structures (Computer science) categories.
Covering the basic paradigms of programming and discussing the many techniques specific to Perl, this guide examines standard data formats--such as text, binary, HTML and XML--before giving tips on creating and parsing new structured data formats. 5 line drawings, 5 tables.
Embedding Perl In Html With Mason
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Author : Dave Rolsky
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2002-10-16
Embedding Perl In Html With Mason written by Dave Rolsky and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-10-16 with Computers categories.
This is the first book to introduce Mason, an open source Perl-based platformwith template elements.
Practical Text Mining With Perl
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Author : Roger Bilisoly
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-20
Practical Text Mining With Perl written by Roger Bilisoly 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 2011-09-20 with Computers categories.
Provides readers with the methods, algorithms, and means to perform text mining tasks This book is devoted to the fundamentals of text mining using Perl, an open-source programming tool that is freely available via the Internet (www.perl.org). It covers mining ideas from several perspectives--statistics, data mining, linguistics, and information retrieval--and provides readers with the means to successfully complete text mining tasks on their own. The book begins with an introduction to regular expressions, a text pattern methodology, and quantitative text summaries, all of which are fundamental tools of analyzing text. Then, it builds upon this foundation to explore: Probability and texts, including the bag-of-words model Information retrieval techniques such as the TF-IDF similarity measure Concordance lines and corpus linguistics Multivariate techniques such as correlation, principal components analysis, and clustering Perl modules, German, and permutation tests Each chapter is devoted to a single key topic, and the author carefully and thoughtfully introduces mathematical concepts as they arise, allowing readers to learn as they go without having to refer to additional books. The inclusion of numerous exercises and worked-out examples further complements the book's student-friendly format. Practical Text Mining with Perl is ideal as a textbook for undergraduate and graduate courses in text mining and as a reference for a variety of professionals who are interested in extracting information from text documents.
The Data Science Design Manual
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Author : Steven S. Skiena
language : en
Publisher: Springer
Release Date : 2017-07-01
The Data Science Design Manual written by Steven S. Skiena and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-01 with Computers categories.
This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)
Perl For Oracle Dbas
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Author : Andy Duncan
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2002
Perl For Oracle Dbas written by Andy Duncan and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Computers categories.
This handbook describes what DBAs need to know about Perl and explains how they can use this popular open source language to manage, monitor, and tune their databases.
Python Data Science Essentials
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Author : Alberto Boschetti
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-10-28
Python Data Science Essentials written by Alberto Boschetti and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-28 with Computers categories.
Become an efficient data science practitioner by understanding Python's key concepts About This Book Quickly get familiar with data science using Python 3.5 Save time (and effort) with all the essential tools explained Create effective data science projects and avoid common pitfalls with the help of examples and hints dictated by experience Who This Book Is For If you are an aspiring data scientist and you have at least a working knowledge of data analysis and Python, this book will get you started in data science. Data analysts with experience of R or MATLAB will also find the book to be a comprehensive reference to enhance their data manipulation and machine learning skills. What You Will Learn Set up your data science toolbox using a Python scientific environment on Windows, Mac, and Linux Get data ready for your data science project Manipulate, fix, and explore data in order to solve data science problems Set up an experimental pipeline to test your data science hypotheses Choose the most effective and scalable learning algorithm for your data science tasks Optimize your machine learning models to get the best performance Explore and cluster graphs, taking advantage of interconnections and links in your data In Detail Fully expanded and upgraded, the second edition of Python Data Science Essentials takes you through all you need to know to suceed in data science using Python. Get modern insight into the core of Python data, including the latest versions of Jupyter notebooks, NumPy, pandas and scikit-learn. Look beyond the fundamentals with beautiful data visualizations with Seaborn and ggplot, web development with Bottle, and even the new frontiers of deep learning with Theano and TensorFlow. Dive into building your essential Python 3.5 data science toolbox, using a single-source approach that will allow to to work with Python 2.7 as well. Get to grips fast with data munging and preprocessing, and all the techniques you need to load, analyse, and process your data. Finally, get a complete overview of principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business users. Style and approach The book is structured as a data science project. You will always benefit from clear code and simplified examples to help you understand the underlying mechanics and real-world datasets.
Python For Data Analysis
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Author : Wes McKinney
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-09-25
Python For Data Analysis written by Wes McKinney and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-25 with Computers categories.
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
Perl Hacks
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Author : Chromatic
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2006
Perl Hacks written by Chromatic and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Computers categories.
A guide to getting the most out of Perl covers such topics as productivity hacks, user interaction, data munging, working with modules, object hacks, and debugging.
Mastering Perl For Bioinformatics
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Author : James Tisdall
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2003-09-25
Mastering Perl For Bioinformatics written by James Tisdall and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-09-25 with Computers categories.
Historically, programming hasn't been considered a critical skill for biologists. But now, with access to vast amounts of biological data contained in public databases, programming skills are increasingly in strong demand in biology research and development. Perl, with its highly developed capacities in string handling, text processing, networking, and rapid prototyping, has emerged as the programming language of choice for biological data analysis.Mastering Perl for Bioinformatics covers the core Perl language and many of its module extensions, presenting them in the context of biological data and problems of pressing interest to the biological community. This book, along with Beginning Perl for Bioinformatics, forms a basic course in Perl programming. This second volume finishes the basic Perl tutorial material (references, complex data structures, object-oriented programming, use of modules--all presented in a biological context) and presents some advanced topics of considerable interest in bioinformatics.The range of topics covered in Mastering Perl for Bioinformatics prepares the reader for enduring and emerging developments in critical areas of bioinformatics programming such as: Gene finding String alignment Methods of data storage and retrieval (SML and databases) Modeling of networks (graphs and Petri nets) Graphics (Tk) Parallelization Interfacing with other programming languages Statistics (PDL) Protein structure determination Biological models of computation (DNA Computers) Biologists and computer scientists who have conquered the basics of Perl and are ready to move even further in their mastery of this versatile language will appreciate the author's well-balanced approach to applying Perl's analytical abilities to the field of bioinformatics. Full of practical examples and real-world biological problem solving, this book is a must for any reader wanting to move beyond beginner level Perl in bioinformatics.
Effective Perl Programming
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Author : Joseph N. Hall
language : en
Publisher: Pearson Education
Release Date : 2010-04-19
Effective Perl Programming written by Joseph N. Hall and has been published by Pearson Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-04-19 with Computers categories.
The Classic Guide to Solving Real-World Problems with Perl—Now Fully Updated for Today’s Best Idioms! For years, experienced programmers have relied on Effective Perl Programming to discover better ways to solve problems with perl. Now, in this long-awaited second edition, three renowned Perl programmers bring together today’s best idioms, techniques, and examples: everything you need to write more powerful, fluent, expressive, and succinct code with Perl. Nearly twice the size of the first edition, Effective Perl Programming, Second Edition, offers everything from rules of thumb to avoid common pitfalls to the latest wisdom for using Perl modules. You won’t just learn the right ways to use Perl: You’ll learn why these approaches work so well. New coverage in this edition includes Reorganized and expanded material spanning twelve years of Perl evolution Eight new chapters on CPAN, databases, distributions, files and filehandles, production Perl, testing, Unicode, and warnings Updates for Perl 5.12, the latest version of Perl Systematically updated examples reflecting today’s best idioms You’ll learn how to work with strings, numbers, lists, arrays, strictures, namespaces, regular expressions, subroutines, references, distributions, inline code, warnings, Perl::Tidy, data munging, Perl one-liners, and a whole lot more. Every technique is organized in the same Items format that helped make the first edition so convenient and popular.