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  • 1
    ISBN: 9788383227528 , 8383227523
    Language: Polish
    Pages: 1 online resource (320 pages) , illustrations
    Edition: [First edition].
    Uniform Title: Introduction to machine learning with Python
    DDC: 005.13/3
    Keywords: Machine learning ; Python (Computer program language) ; Data mining
    Abstract: Uczenie maszynowe kojarzy się z dużymi firmami i rozbudowanymi zespołami. Prawda jest taka, że obecnie można samodzielnie budować zaawansowane rozwiązania uczenia maszynowego i korzystać do woli z olbrzymich zasobów dostępnych danych. Trzeba tylko mieć pomysł i... trochę podstawowej wiedzy. Tymczasem większość opracowań na temat uczenia maszynowego i sztucznej inteligencji wymaga biegłości w zaawansowanej matematyce. Utrudnia to naukę tego zagadnienia, mimo że uczenie maszynowe jest coraz powszechniej stosowane w projektach badawczych i komercyjnych. Ta praktyczna książka ułatwi Ci rozpoczęcie wdrażania rozwiązań rzeczywistych problemów związanych z uczeniem maszynowym. Zawiera przystępne wprowadzenie do uczenia maszynowego i sztucznej inteligencji, a także sposoby wykorzystania Pythona i biblioteki scikit-learn, uwzględniające potrzeby badaczy i analityków danych oraz inżynierów pracujących nad aplikacjami komercyjnymi. Zagadnienia matematyczne ograniczono tu do niezbędnego minimum, zamiast tego skoncentrowano się na praktycznych aspektach algorytmów uczenia maszynowego. Dokładnie opisano, jak konkretnie można skorzystać z szerokiej gamy modeli zaimplementowanych w dostępnych bibliotekach.
    Note: Includes index
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  • 2
    Language: German
    Pages: 1 online resource (1 volume) , illustrations
    Edition: 1. Auflage 2017.
    Keywords: Machine learning ; Python (Computer program language) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Machine Learning ist zu einem wichtigen Bestandteil vieler kommerzieller Anwendungen und Forschungsprojekte geworden, von der medizinischen Diagnostik bis hin zur Suche nach Freunden in sozialen Netzwerken. Um Machine Learning-Anwendungen selbst zu entwickeln, braucht es keine großen Teams: Wenn Sie Python-Grundkenntnisse mitbringen, kann Ihnen dieses Praxisbuch zeigen, wie Sie Ihre eigenen Machine Learning-Lösungen entwickeln.Mit Python und der scikit-learn-Bibliothek erarbeiten Sie sich alle Schritte, die für eine erfolgreiche Machine Learning-Anwendung notwendig sind. Die Autoren Andreas Müller und Sarah Guido konzentrieren sich bei der Verwendung von Machine Learning-Algorithmen auf die Praxis und weniger auf die Mathematik dahinter. Wenn Sie zusätzlich mit den Bibliotheken NumPy und matplotlib vertraut sind, hilft Ihnen dies, noch mehr aus diesem Buch herauszuholen.
    Note: Includes index. - Description based on online resource; title from title page (viewed November 1, 2017)
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  • 3
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Programming languages (Electronic computers) ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. With this book, you'll learn: Fundamental concepts and applications of machine learning Advantages and shortcomings of widely used machine learning algorithms How to represent data processed by machine learning, including which data aspects to focus on Advanced methods for model evaluation and parameter tuning The concept of pipelines for chaining models and encapsulating your workflow Methods for working with text data, including text-specific processing techniques Suggestions for improving your machine learning and data science skills
    Note: Includes index. - Description based on online resource; title from title page (viewed October 6, 2016)
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  • 4
    ISBN: 9781771374927
    Language: English
    Pages: 1 online resource (1 streaming video file (3 hr., 44 min., 6 sec.)) , digital, sound, color
    Keywords: Machine learning ; Python (Computer program language) ; Electronic videos ; local
    Abstract: "In this Advanced Machine Learning with scikit-learn training course, expert author Andreas Mueller will teach you how to choose and evaluate machine learning models. This course is designed for users that already have experience with Python. You will start by learning about model complexity, overfitting and underfitting. From there, Andreas will teach you about pipelines, advanced metrics and imbalanced classes, and model selection for unsupervised learning. This video tutorial also covers dealing with categorical variables, dictionaries, and incomplete data, and how to handle text data. Finally, you will learn about out of core learning, including the sci-learn interface for out of core learning and kernel approximations for large-scale non-linear classification. Once you have completed this computer based training course, you will have learned everything you need to know to be able to choose and evaluate machine learning models. Working files are included, allowing you to follow along with the author throughout the lessons. "--Resource description page.
    Note: Title from title screen (viewed October 26, 2015). - Date of publication from resource description page
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  • 5
    Title: 精通機器學習 : : 使用 Python = Introduction to machine learning with Python /
    ISBN: 9789864763665 , 9864763660
    Language: Chinese
    Pages: 1 online resource (384 pages) , illustrations
    Edition: [First edition].
    Uniform Title: Introduction to machine learning with Python
    DDC: 005.13/3
    Keywords: Machine learning ; Python (Computer program language) ; Data mining ; Data Mining ; Apprentissage automatique ; Python (Langage de programmation) ; Exploration de données (Informatique) ; Data mining ; Machine learning ; Python (Computer program language) ; Electronic books
    Abstract: Detailed summary in vernacular field.
    Note: Includes index
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  • 6
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : Posts & Telecom Press
    ISBN: 9787115475619 , 711547561X
    Language: Undetermined
    Pages: 1 online resource
    Note: Title from content provider
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