Deep Learning with Structured Data

Mark Ryan

ISBN 10: 1617296724 / ISBN 13: 9781617296727

Published by Manning Publications Dez 2020, 2020

About this Item

Neuware - Deep Learning with Structured Data teaches you powerful data analysis techniques for tabular data and relational databases.SummaryDeep 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.About the technologyHere 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 bookDeep 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 insideWhen and where to use deep learningThe architecture of a Keras deep learning modelTraining, deploying, and maintaining modelsMeasuring performanceAbout the readerFor readers with intermediate Python and machine learning skills.About the authorMark 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 Contents1 Why deep learning with structured data 2 Introduction to the example problem and Pandas dataframes3 Preparing the data, part 1: Exploring and cleansing the data4 Preparing the data, part 2: Transforming the data5 Preparing and building the model6 Training the model and running experiments7 More experiments with the trained model8 Deploying the model9 Recommended next steps.

Seller Inventory # 9781617296727

Bibliographic Details

• Title: Deep Learning with Structured Data
• Publisher: Manning Publications Dez 2020
• Publication Date: 2020
• Language: English
• ISBN 10: 1617296724
• ISBN 13: 9781617296727
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 231W x 185H x 18D millimeters 231 millimeters width by 185 millimeters height by 18 millimeters depth
• Weight: 440 grams

About this title

Synopsis

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.

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

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.