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BOOK DATA SCIENCE USING ORACLE DATA MINER AND ORACLE R ENTERPRISE
SUMMARY
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Items Found: 288
- roduction
- Chapter 1: Getting Started With Oracle Advanced Analytics
- Data Science
- Business Understanding
- Data Understanding
- Data Preparation
- Modeling
- Evaluation
- Deployment
- Machine Learning
- Supervised Learning
- Unsupervised Learning
- Getting Started with Oracle Advanced Analytics
- Oracle Data Miner
- R Technologies in Oracle
- Oracle R Enterprise
- Advantages of using Oracle R Enterprise
- Analytical SQL and PLSQL Functions
- Package DBMS_STATS_FUNC
- SQL Functions
- Chapter 2: Installation and Hello World
- Booting Up Oracle Data Miner
- Installation Prerequisites
- Installation
- Welcome to the World—Oracle Data Miner
- SQL Developer Components for ODM
- ODM Data Dictionary
- Boot Up Oracle R Enterprise
- Prerequisites
- Oracle R Distribution
- Oracle R Enterprise Server Installation
- Oracle R Enterprise Client Installation
- Install Supporting Packages for the ORE Client
- Welcome to the World of Oracle R Enterprise
- ORE Data Dictionary
- Chapter 3: Clustering Methods
- Clustering Approaches
- The k-means Algorithm
- k-means in Oracle Advanced Analytics
- Clustering Rules Evaluation Metrics
- Parameters to Tune k-means Clustering
- Creating a Cluster Model in Oracle Advanced Analytics
- Clustering using SQL and PLSQL
- Case Study—Customer Segmentation
- Business understanding
- Data understanding
- RFM Segmentation—Data Preparation
- RFM Segmentation—DATA Modeling
- Need-Based Segmentation—Data Preparation
- Need-Based Segmentation—Data Modeling
- Result Evaluation
- Deployment—Storing the Results Back to the Database
- Assigning Segments to New Customers
- Chapter 4: Association Rules
- Introduction to Association Rules
- Terminologies Associated with Association Rules
- Working of an Apriori Algorithm
- Identify Interesting Rules
- Algorithm Settings
- Model Settings
- Association Rules Using SQL and PLSQL
- Creating the Association Rules Model Using Oracle R Enterprise
- Creating the Association Model Using SQL Developer
- Case Study—Market Basket Analysis
- Business Understanding
- Data Understanding
- Data Preparation
- Data Modeling
- High-Level Technical Overview
- Execution
- Chapter 5: Regression Analysis
- Understanding Relationships
- Regression Analysis
- Working of OLS Regression
- Assumptions of OLS
- OLS Regression in Oracle Advanced Analytics
- GLM Regression
- Ridge Regression
- Parameters to Tune the GLM Model
- GLM and Ridge Regression in Oracle Advanced Analytics
- GLM Regression Using SQL and PLSQL
- Creating GLM Regression Using Oracle R Enterprise
- Creating GLM and Ridge Regression from SQL Developer
- Guidelines for Regression Modeling
- Case Study: Sales Forecasting
- Business Understanding
- Data Understanding
- Data Preparation
- Data Modeling
- Chapter 6: Classification Methods
- Overview of Classification Techniques
- Logistic Regression
- Naïve Bayes
- Creating a Naïve Bayes Model Using SQL and PLSQL
- Creating a Naïve Bayes Classifier Using Oracle R Enterprise
- Assessing the Model Quality for Classifiers
- Decision Trees
- Entropy and Information Gain
- Information Gain
- Pruning Methods/Early Stopping Criteria for Decision Trees
- Parameters to Tune a Decision Tree Model
- Decision Tree Modeling Using SQL and PLSQL
- Decision Tree Modeling Using Oracle R Enterprise
- SVM
- Parameters to Tune the SVM Model
- SVM Using SQL and PLSQL
- SVM Using Oracle R Enterprise
- A Few Other Important PLSQL APIs for Classifiers
- Choosing a Classifier
- Case Study: Customer Churn Prediction
- Business Understanding
- Data Understanding
- Data Preparation
- Data Modeling
- Selecting the Best Classifier
- Results Interpretation
- Chapter 7: Advanced Topics
- Overview of Neural Networks
- Function of a Hidden Layer Neuron
- Parameters for Neural Network
- Neural Network Using Oracle Advanced Analytics
- Overview of Anomaly Detection
- One-Class SVM
- Anomaly Detection Using Oracle Advanced Analytics
- Overview of Predictive Analytics in Oracle Advanced Analytics
- Predictive Analytics Using SQL Developer GUI
- DBMS_PREDICTIVE_ANALYTICS
- EXPLAIN
- PREDICT
- PROFILE
- Overview of Product Recommendation Engine
- Product Recommendation Engine Using Oracle Advanced Analytics
- Overview of Random Forest
- Random Forest Using Oracle Advanced Analytics
- Chapter 8: Solutions Deployment
- Export and Import an ODM Workflow
- Deploy Option for Data Miner Workflows in SQL Developer
- Import and Export Data Mining Models
- EXPORT_MODEL
- IMPORT_MODEL
- Renaming Models
- Drop Models
- Predictive Model Markup Language (PMML)
- Importing and Exporting PMML models into Oracle Advanced Analytics
- roduction
- Chapter 1: Getting Started With Oracle Advanced Analytics
- Data Science
- Business Understanding
- Data Understanding
- Data Preparation
- Modeling
- Evaluation
- Deployment
- Machine Learning
- Supervised Learning
- Unsupervised Learning
- Getting Started with Oracle Advanced Analytics
- Oracle Data Miner
- R Technologies in Oracle
- Oracle R Enterprise
- Advantages of using Oracle R Enterprise
- Analytical SQL and PLSQL Functions
- Package DBMS_STATS_FUNC
- SQL Functions
- Chapter 2: Installation and Hello World
- Booting Up Oracle Data Miner
- Installation Prerequisites
- Installation
- Welcome to the World—Oracle Data Miner
- SQL Developer Components for ODM
- ODM Data Dictionary
- Boot Up Oracle R Enterprise
- Prerequisites
- Oracle R Distribution
- Oracle R Enterprise Server Installation
- Oracle R Enterprise Client Installation
- Install Supporting Packages for the ORE Client
- Welcome to the World of Oracle R Enterprise
- ORE Data Dictionary
- Chapter 3: Clustering Methods
- Clustering Approaches
- The k-means Algorithm
- k-means in Oracle Advanced Analytics
- Clustering Rules Evaluation Metrics
- Parameters to Tune k-means Clustering
- Creating a Cluster Model in Oracle Advanced Analytics
- Clustering using SQL and PLSQL
- Case Study—Customer Segmentation
- Business understanding
- Data understanding
- RFM Segmentation—Data Preparation
- RFM Segmentation—DATA Modeling
- Need-Based Segmentation—Data Preparation
- Need-Based Segmentation—Data Modeling
- Result Evaluation
- Deployment—Storing the Results Back to the Database
- Assigning Segments to New Customers
- Chapter 4: Association Rules
- Introduction to Association Rules
- Terminologies Associated with Association Rules
- Working of an Apriori Algorithm
- Identify Interesting Rules
- Algorithm Settings
- Model Settings
- Association Rules Using SQL and PLSQL
- Creating the Association Rules Model Using Oracle R Enterprise
- Creating the Association Model Using SQL Developer
- Case Study—Market Basket Analysis
- Business Understanding
- Data Understanding
- Data Preparation
- Data Modeling
- High-Level Technical Overview
- Execution
- Chapter 5: Regression Analysis
- Understanding Relationships
- Regression Analysis
- Working of OLS Regression
- Assumptions of OLS
- OLS Regression in Oracle Advanced Analytics
- GLM Regression
- Ridge Regression
- Parameters to Tune the GLM Model
- GLM and Ridge Regression in Oracle Advanced Analytics
- GLM Regression Using SQL and PLSQL
- Creating GLM Regression Using Oracle R Enterprise
- Creating GLM and Ridge Regression from SQL Developer
- Guidelines for Regression Modeling
- Case Study: Sales Forecasting
- Business Understanding
- Data Understanding
- Data Preparation
- Data Modeling
- Chapter 6: Classification Methods
- Overview of Classification Techniques
- Logistic Regression
- Naïve Bayes
- Creating a Naïve Bayes Model Using SQL and PLSQL
- Creating a Naïve Bayes Classifier Using Oracle R Enterprise
- Assessing the Model Quality for Classifiers
- Decision Trees
- Entropy and Information Gain
- Information Gain
- Pruning Methods/Early Stopping Criteria for Decision Trees
- Parameters to Tune a Decision Tree Model
- Decision Tree Modeling Using SQL and PLSQL
- Decision Tree Modeling Using Oracle R Enterprise
- SVM
- Parameters to Tune the SVM Model
- SVM Using SQL and PLSQL
- SVM Using Oracle R Enterprise
- A Few Other Important PLSQL APIs for Classifiers
- Choosing a Classifier
- Case Study: Customer Churn Prediction
- Business Understanding
- Data Understanding
- Data Preparation
- Data Modeling
- Selecting the Best Classifier
- Results Interpretation
- Chapter 7: Advanced Topics
- Overview of Neural Networks
- Function of a Hidden Layer Neuron
- Parameters for Neural Network
- Neural Network Using Oracle Advanced Analytics
- Overview of Anomaly Detection
- One-Class SVM
- Anomaly Detection Using Oracle Advanced Analytics
- Overview of Predictive Analytics in Oracle Advanced Analytics
- Predictive Analytics Using SQL Developer GUI
- DBMS_PREDICTIVE_ANALYTICS
- EXPLAIN
- PREDICT
- PROFILE
- Overview of Product Recommendation Engine
- Product Recommendation Engine Using Oracle Advanced Analytics
- Overview of Random Forest
- Random Forest Using Oracle Advanced Analytics
- Chapter 8: Solutions Deployment
- Export and Import an ODM Workflow
- Deploy Option for Data Miner Workflows in SQL Developer
- Import and Export Data Mining Models
- EXPORT_MODEL
- IMPORT_MODEL
- Renaming Models
- Drop Models
- Predictive Model Markup Language (PMML)
- Importing and Exporting PMML models into Oracle Advanced Analytics
