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Feature engineering for machine learning : principles and techniques for data scientists

By: Alice, ZhengContributor(s): Casari, AmandaMaterial type: Text

TextPublication details: Mumbai Shroff publishers 2018Description: xiii, 200 pages : illustrationsISBN: 9789352137114Subject(s): Data mining | Machine learningDDC classification: 006.31 Summary: Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, youll learn techniques for extracting and transforming featuresthe numeric representations of raw datainto formats for machine-learning models. Each chapter guides you through a single data problem, such as how to represent text or image data. Together, these examples illustrate the main principles of feature engineering.--

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Item type	Current library	Collection	Call number	Status	Date due	Barcode
BK	Kannur University Central Library Stack	Stack	006.31 ALI/F (Browse shelf (Opens below))	Available		68237

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Previous	006.3 THU/D Data mining: technologies, techniques, tools and trends	006.301 RAJ/A Artificial intelligence and the future of power : 5 battlegrounds	006.310 151 STA/G Gentle introduction to support vector machines in biomedicine	006.31 ALI/F Feature engineering for machine learning : principles and techniques for data scientists	006.31 ALP/M introduction to machine learning	006.31 ANI/P Practical Deep Learning for Cloud, Mobile, and Edge real-world AI & computer-vision projects using python, keras & tensorflow	006.31 BON/B Building machine learning projects with TensorFlow : engaging projects that will teach you how complex data can be exploited to gain the most insight /	Next

Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, youll learn techniques for extracting and transforming featuresthe numeric representations of raw datainto formats for machine-learning models. Each chapter guides you through a single data problem, such as how to represent text or image data. Together, these examples illustrate the main principles of feature engineering.--

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