Data Science Using Oracle Data Miner and Oracle R Enterprise

Sibanjan is a Sr Analyst for Business Intelligence and Data Science evangelist. He has a strong consulting experience on Business Systems and Data Analytics. As a highly empowered consultant offering around 7 yrs of cross functional experience in the industry, he has helped several organizations to improve, automate and operationalize analytics for their business processes. He comes with a background of implementing business processes using Oracle ERP systems and predictive analytics solutions using Oracle Data Miner and Oracle R Enterprise. He is a Master of Business Analytics from Singapore Management University and holds several certification credentials such as OCA, OCP, ITIL V3, CSCMS and Six Sigma Green belt.

Introduction Chapter 1 : Getting Started with Oracle Advanced Analytics Overview of Data Science and CRISP-DM MethodologyOverview of machine learning and its application in industriesGetting started with Oracle Advanced Analytics- Oracle Data Miner and Oracle R EnterpriseAnalytical SQL and PL/SQL functionsSummary Chapter 2 : Installation and Hello World Oracle Data Miner InstallationSample Hello World Oracle Data Miner workflowOracle Data Miner components for SQL Developer GUIOracle R Enterprise InstallationSample Hello World program using Oracle RSummaryChapter 3: Clustering Methods Approaches for cluster analysisK-means algorithm fundamentalsK-means algorithm in Oracle Advanced AnalyticsMetrics for evaluating clustering algorithmsCreate clusters using Oracle SQL and PLSQL API'sCreate clusters using Oracle R EnterpriseCreate clusters using Oracle SQL Developer GUICase Study - Customer SegmentationSummaryChapter 4: Association Rules Introduction to association rulesTerminologies associated with association rulesApriori algorithm fundamentalsIdentify interesting rulesAssociation rules using Oracle SQL and PLSQL API'sAssociation rules using Oracle R EnterpriseAssociation rules using Oracle SQL Developer GUICase Study - Market Basket AnalysisSummaryChapter 5: Regression Analysis Understanding RelationshipsIntroduction to Regression AnalysisOLS Regression fundamentalsOLS Regression using Oracle Advanced AnalyticsGLM and Ridge Regression OverviewGLM Regression using Oracle SQL and PLSQL API'sGLM Regression using Oracle R EnterpriseGLM Regression using Oracle SQL Developer GUICase Study - Sales ForecastSummaryChapter 6: Classification Techniques Overview of classification techniquesLogistics Regression fundamentalsDecision Tree fundamentalsSVM fundamentalsNaive Bayes fundamentalsClassification using Oracle Advanced AnalyticsClassification using Oracle SQL and PLSQL API'sClassification using Oracle R EnterpriseClassification using Oracle SQL Developer GUICase Study - Customer Churn PredictionSummary Chapter 7: Advanced Topics Overview of Neural NetworksNeural Network using Oracle Advanced AnalyticsOverview of Anomaly detectionAnomaly detection using Oracle Advanced AnalyticsOverview of Random ForestRandom Forest using Oracle Advanced AnalyticsOverview of Predictive QueriesPredictive Queries using Oracle Advanced AnalyticsOverview of Product Recommendation EngineProduct Recommendation engine using Oracle Advanced AnalyticsSummaryChapter 8: Solution Deployment Oracle Data Miner Import and Export functionalityIntroduction to PMMLGenerating PMML from Oracle Advanced Analytics models