Predictive Analytics

Foreword <br> Chapter 1 Introduction to Analytics <br>What's in a Name? <br>Why the Sudden Popularity of Analytics and Data Science? <br>The Application Areas of Analytics <br>The Main Challenges of Analytics <br>A Longitudinal View of Analytics <br>A Simple Taxonomy for Analytics <br>The Cutting Edge of Analytics: IBM Watson <br>Summary <br>References <br> Chapter 2 Introduction to Predictive Analytics and Data Mining <br>What Is Data Mining? <br>What Data Mining Is Not <br>The Most Common Data Mining Applications <br>What Kinds of Patterns Can Data Mining Discover? <br>Popular Data Mining Tools <br>The Dark Side of Data Mining: Privacy Concerns <br>Summary <br>References <br> Chapter 3 Standardized Processes for Predictive Analytics <br>The Knowledge Discovery in Databases (KDD) Process <br>Cross-Industry Standard Process for Data Mining (CRISP-DM) <br>SEMMA <br>SEMMA Versus CRISP-DM <br>Six Sigma for Data Mining <br>Which Methodology Is Best? <br>Summary <br>References <br> Chapter 4 Data and Methods for Predictive Analytics <br>The Nature of Data in Data Analytics <br>Preprocessing of Data for Analytics <br>Data Mining Methods <br>Prediction <br>Classification <br>Decision Trees <br>Cluster Analysis for Data Mining <br>k-Means Clustering Algorithm <br>Association <br>Apriori Algorithm <br>Data Mining and Predictive Analytics Misconceptions and Realities <br>Summary <br>References <br> Chapter 5 Algorithms for Predictive Analytics <br>Naive Bayes <br>Nearest Neighbor <br>Similarity Measure: The Distance Metric <br>Artificial Neural Networks <br>Support Vector Machines <br>Linear Regression <br>Logistic Regression <br>Time-Series Forecasting <br>Summary <br>References <br> Chapter 6 Advanced Topics in Predictive Modeling <br>Model Ensembles <br>Bias–Variance Trade-off in Predictive Analytics <br>Imbalanced Data Problems in Predictive Analytics <br>Explainability of Machine Learning Models for <br>Predictive Analytics <br>Summary <br>References <br> Chapter 7 Text Analytics, Topic Modeling, and Sentiment Analysis <br>Natural Language Processing <br>Text Mining Applications <br>The Text Mining Process <br>Text Mining Tools <br>Topic Modeling <br>Sentiment Analysis <br>Summary <br>References <br> Chapter 8 Big Data for Predictive Analytics <br>Where Does Big Data Come From? <br>The Vs That Define Big Data <br>Fundamental Concepts of Big Data <br>The Business Problems That Big Data Analytics <br>Addresses <br>Big Data Technologies <br>Data Scientists <br>Big Data and Stream Analytics <br>Data Stream Mining <br>Summary <br>References <br> Chapter 9 Deep Learning and Cognitive Computing <br>Introduction to Deep Learning <br>Basics of “Shallow” Neural Networks <br>Elements of an Artificial Neural Network <br>Deep Neural Networks <br>Convolutional Neural Networks <br>Recurrent Networks and Long Short-Term Memory Networks <br>Computer Frameworks for Implementation of Deep Learning <br>Cognitive Computing <br>Summary <br>References <br> Appendix A KNIME and the Landscape of Tools for Business Analytics and Data Science <br> <br> <br>9780136738510&nbsp;&nbsp; TOC&nbsp;&nbsp;&nbsp; 11/12/2020 <br> <br> <br>