deep learning structured data de ryan mark (17 résultats)

Paperback. Etat : Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Etat : very_good. Fast Free Shipping â" Very Good condition book with a firm cover and clean pages. Shows normal use and some light wear or limited notes markings. A solid, nice copy to enjoy.

paperback. Etat : Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!

Etat : As New. Unread copy in mint condition.

Etat : New. Brand New.

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.

Paperback. Etat : new. Paperback. 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. "For readers with intermediate Python and machine learning skills"--Back cover. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

Etat : New. pp. 325.

Etat : New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Etat : New. pp. 325.

Etat : New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.

Etat : New. pp. 325.

Paperback. Etat : new. Paperback. 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. "For readers with intermediate Python and machine learning skills"--Back cover. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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.

Kartoniert / Broschiert. Etat : New. &Uumlber den AutorMark 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.Klappentext.

Taschenbuch. Etat : Neu. Neuware - Deep Learning with Structured Data teaches you powerful data analysis techniques for tabular data and relational databases.Summary 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. Purchase of the print book includes a free Elektronisches Buch in PDF, Kindle, and ePub formats from Manning Publications. About the technology Here's a dirty secret: Half of the time in most data science projects is spent cleaning and preparing data. But there's a better way: Deep learning techniques optimized for tabular data and relational databases deliver insights and analysis without requiring intense feature engineering. Learn the skills to unlock deep learning performance with much less data filtering, validating, and scrubbing. About the book Deep Learning with Structured Data teaches you powerful data analysis techniques for tabular data and relational databases. Get started using a dataset based on the Toronto transit system. As you work through the book, you'll learn how easy it is to set up tabular data for deep learning, while solving crucial production concerns like deployment and performance monitoring. What's inside When and where to use deep learning The architecture of a Keras deep learning model Training, deploying, and maintaining models Measuring performance About the reader For readers with intermediate Python and machine learning skills. About the author Mark Ryan is a Data Science Manager at Intact Insurance. He holds a Master's degree in Computer Science from the University of Toronto. Table of Contents 1 Why deep learning with structured data 2 Introduction to the example problem and Pandas dataframes 3 Preparing the data, part 1: Exploring and cleansing the data 4 Preparing the data, part 2: Transforming the data 5 Preparing and building the model 6 Training the model and running experiments 7 More experiments with the trained model 8 Deploying the model 9 Recommended next steps.