Most businesses are far more interested in accurate forecasting and fraud detection using their existing structured datasets than identifying cats in YouTube videos. Powerful deep learning techniques can efficiently extract insight from the kind of structured data collected by most businesses and organisations.
Deep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts.
Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind of structured, tabular data you'll find in the relational databases that real-world businesses depend on. Filled with practical, relevant applications, this book teaches you how deep learning can augment your existing machine learning and business intelligence systems.
• The benefits and drawbacks of deep learning
• Organizing data for your deep learning model
• The deep learning stack
• Measuring performance of your models
For readers with an intermediate knowledge of Python, Jupyter notebooks, and machine learning.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Mark Ryan has 20 years of experience leading teams delivering IBM’s premier relational database product. He holds a Master's degree in Computer Science from the University of Toronto.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Paperback. Etat : New. Most businesses are far more interested in accurate forecasting and fraud detection using their existing structured datasets than identifying cats in YouTube videos. Powerful deep learning techniques can efficiently extract insight from the kind of structured data collected by most businesses and organisations. Deep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind of structured, tabular data you'll find in the relational databases that real-world businesses depend on. Filled with practical, relevant applications, this book teaches you how deep learning can augment your existing machine learning and business intelligence systems. . The benefits and drawbacks of deep learning . Organizing data for your deep learning model . The deep learning stack . Measuring performance of your models For readers with an intermediate knowledge of Python, Jupyter notebooks, and machine learning. N° de réf. du vendeur LU-9781617296727
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