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Python Machine Learning

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From automated speech recognition on smartphones to email spam filters and movie recommendation systems, machine learning is integral to modern applications. The rise of powerful open-source libraries has made machine learning accessible to all, with Python serving as an ideal platform for developing these systems efficiently. This resource will guide you through the fundamentals of machine learning and its practical applications using Python. You will learn step-by-step best practices for transforming raw data into valuable insights, efficiently developing learning algorithms, and evaluating outcomes. The content covers various problem categories that machine learning addresses, including object classification, regression analysis for predicting continuous outcomes, and clustering to uncover hidden data structures. Additionally, you will create a sentiment analysis machine learning system and learn how to integrate your model into a web application to share with others.

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Python Machine Learning, Sebastian Raschka, Randal S. Olson

Idioma
Publicado en
2015
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Título
Python Machine Learning
Idioma
Inglés
Publicado en
2015
Formato
Tapa blanda
Páginas
454
ISBN10
1783555130
ISBN13
9781783555130
Serie
Calificación
4,25 de 5
Descripción
From automated speech recognition on smartphones to email spam filters and movie recommendation systems, machine learning is integral to modern applications. The rise of powerful open-source libraries has made machine learning accessible to all, with Python serving as an ideal platform for developing these systems efficiently. This resource will guide you through the fundamentals of machine learning and its practical applications using Python. You will learn step-by-step best practices for transforming raw data into valuable insights, efficiently developing learning algorithms, and evaluating outcomes. The content covers various problem categories that machine learning addresses, including object classification, regression analysis for predicting continuous outcomes, and clustering to uncover hidden data structures. Additionally, you will create a sentiment analysis machine learning system and learn how to integrate your model into a web application to share with others.