0.3 Book Content and Organization

This book will cover practical examples of some of the most common practices in each phase of the Cross-Platform Industry Standard for Data Mining (CRISP-DM) methodology. The chapters can be categorized based on the CRISP-DM phase they commonly apply to:

  • Pre-CRISP-DM Introductory Concepts

    • Ch1: Introduction to Data Mining

    • Ch2: Data Mining Project Methodology

  • CRISP-DM: Data Understanding phase

    • Ch3: Visualization: Theory and Design

    • Ch4: Tableau: Core Features

    • Ch5: Tableau: Exploratory Data Analysis

    • Ch6: Tableau: Clustering

    • Ch7: Excel: Multivariate Prediction

  • CRISP-DM: Data Preparation phase

    • Ch8: ML Studio: Introduction to Pipelines

    • Ch9: ML Studio: Data Cleaning and Preparation

  • CRISP-DM: Modeling phase

    • Ch10: ML Studio: Selecting the Features

    • Ch11: Modeling: Algorithm Selection

    • Ch12: ML Studio: Optimizing Model Fit and Performance

    • Ch13: ML Studio: Text Analytics

    • Ch14: Recommended Engines: Matchbox Recommender

    • Ch15: Project: Putting It All Together

  • Supplement: The New Azure ML Portal

  • Supplement: Tableau: JavaScript API

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