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Building Machine Learning Systems with Python, Chaffer J


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Цена: 10114.00р.
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Автор: Chaffer J
Название:  Building Machine Learning Systems with Python
ISBN: 9781782161400
Издательство: Packt Publishing
Классификация:

ISBN-10: 1782161406
Обложка/Формат: Paperback
Страницы: 290
Вес: 0.50 кг.
Дата издания: 30.09.2013
Язык: English
Размер: 234 x 192 x 15
Рейтинг:
Поставляется из: США
Описание:

Expand your Python knowledge and learn all about machine-learning libraries in this user-friendly manual. ML is the next big breakthrough in technology and this book will give you the head-start you need.

Key Features

  • Master Machine Learning using a broad set of Python libraries and start building your own Python-based ML systems
  • Covers classification, regression, feature engineering, and much more guided by practical examples
  • A scenario-based tutorial to get into the right mind-set of a machine learner (data exploration) and successfully implement this in your new or existing projects

Book Description

Machine learning, the field of building systems that learn from data, is exploding on the Web and elsewhere. Python is a wonderful language in which to develop machine learning applications. As a dynamic language, it allows for fast exploration and experimentation and an increasing number of machine learning libraries are developed for Python.

Building Machine Learning system with Python shows you exactly how to find patterns through raw data. The book starts by brushing up on your Python ML knowledge and introducing libraries, and then moves on to more serious projects on datasets, Modelling, Recommendations, improving recommendations through examples and sailing through sound and image processing in detail.

Using open-source tools and libraries, readers will learn how to apply methods to text, images, and sounds. You will also learn how to evaluate, compare, and choose machine learning techniques.

Written for Python programmers, Building Machine Learning Systems with Python teaches you how to use open-source libraries to solve real problems with machine learning. The book is based on real-world examples that the user can build on.


Readers will learn how to write programs that classify the quality of StackOverflow answers or whether a music file is Jazz or Metal. They will learn regression, which is demonstrated on how to recommend movies to users. Advanced topics such as topic modeling (finding a texts most important topics), basket analysis, and cloud computing are covered as well as many other interesting aspects.

Building Machine Learning Systems with Python will give you the tools and understanding required to build your own systems, which are tailored to solve your problems.

What you will learn

  • Build a classification system that can be applied to text, images, or sounds
  • Use scikit-learn, a Python open-source library for machine learning
  • Explore the mahotas library for image processing and computer vision
  • Build a topic model of the whole of Wikipedia
  • Get to grips with recommendations using the basket analysis
  • Use the Jug package for data analysis
  • Employ Amazon Web Services to run analyses on the cloud
  • Recommend products to users based on past purchases



Routledge Companion to Commedia Dell`arte

Автор: Chaffee Judith
Название: Routledge Companion to Commedia Dell`arte
ISBN: 1138224995 ISBN-13(EAN): 9781138224995
Издательство: Taylor&Francis
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Цена: 7348.00 р.
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Описание: From Commedia dell’Arte came archetypal characters that are still with us today, such as Harlequin and Pantalone, and the rediscovered craft of writing comic dramas and masked theatre. From it came the forces that helped create and influence Opera, Ballet, Pantomime, Shakespeare, Moliere, Lopes de Vega, Goldoni, Meyerhold, and even the glove puppet, Mr Punch.The Routledge Companion to Commedia dell’Arte is a wide-ranging volume written by over 50 experts, that traces the history, characteristics, and development of this fascinating yet elusive theatre form. In synthesizing the elements of Commedia, this book introduces the history of the Sartori mask studio; presents a comparison between Gozzi and Goldoni’s complicated and adversarial approaches to theatre; invites discussions on Commedia’s relevance to Shakespeare, and illuminates re-interpretations of Commedia in modern times. The authors are drawn from actors, mask-makers, pedagogues, directors, trainers and academics, all of whom add unique insights into this most delightful of theatre styles. Notable contributions include:•       Donato Sartori on the 20th century Sartori mask•       Rob Henke on form and freedom•       Anna Cottis on Carlo Boso•       Didi Hopkins on One Man, Two Guv’nors   •       Kenneth Richards on acting companies•       Antonio Fava on Pulcinella•       Joan Schirle on Carlo Mazzone-Clementi and women in Commedia•       and M.A. Katritzky on images


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