UsefulLinks
Computer Science
Data Science
Predictive Analytics
1. Foundations of Predictive Analytics
2. Data Foundation and Preparation
3. Regression Modeling
4. Classification Modeling
5. Ensemble Methods
6. Neural Networks and Deep Learning
7. Time Series Analysis and Forecasting
8. Unsupervised Learning
9. Model Evaluation and Validation
10. Model Interpretability and Explainability
11. Model Deployment and Production
12. Business Applications and Use Cases
13. Ethics and Responsible AI
12.
Business Applications and Use Cases
12.1.
Customer Analytics
12.1.1.
Customer Segmentation
12.1.1.1.
Behavioral Segmentation
12.1.1.2.
Demographic Segmentation
12.1.1.3.
Value-based Segmentation
12.1.2.
Churn Prediction
12.1.2.1.
Churn Definition
12.1.2.2.
Feature Engineering for Churn
12.1.2.3.
Retention Strategies
12.1.3.
Customer Lifetime Value
12.1.3.1.
CLV Calculation Methods
12.1.3.2.
Predictive CLV Models
12.1.3.3.
Business Applications
12.1.4.
Recommendation Systems
12.1.4.1.
Collaborative Filtering
12.1.4.2.
Content-based Filtering
12.1.4.3.
Hybrid Approaches
12.2.
Financial Services
12.2.1.
Credit Risk Assessment
12.2.1.1.
Credit Scoring Models
12.2.1.2.
Default Prediction
12.2.1.3.
Regulatory Compliance
12.2.2.
Fraud Detection
12.2.2.1.
Transaction Monitoring
12.2.2.2.
Anomaly Detection
12.2.2.3.
Real-time Scoring
12.2.3.
Algorithmic Trading
12.2.3.1.
Price Prediction
12.2.3.2.
Trading Signal Generation
12.2.3.3.
Risk Management
12.2.4.
Insurance Analytics
12.2.4.1.
Risk Assessment
12.2.4.2.
Premium Pricing
12.2.4.3.
Claims Prediction
12.3.
Retail and E-commerce
12.3.1.
Demand Forecasting
12.3.1.1.
Sales Prediction
12.3.1.2.
Inventory Optimization
12.3.1.3.
Seasonal Adjustments
12.3.2.
Price Optimization
12.3.2.1.
Dynamic Pricing
12.3.2.2.
Competitive Analysis
12.3.2.3.
Elasticity Modeling
12.3.3.
Supply Chain Analytics
12.3.3.1.
Supplier Risk Assessment
12.3.3.2.
Logistics Optimization
12.3.3.3.
Demand Planning
12.4.
Manufacturing and Operations
12.4.1.
Predictive Maintenance
12.4.1.1.
Equipment Failure Prediction
12.4.1.2.
Maintenance Scheduling
12.4.1.3.
Cost Optimization
12.4.2.
Quality Control
12.4.2.1.
Defect Prediction
12.4.2.2.
Process Optimization
12.4.2.3.
Statistical Process Control
12.4.3.
Production Planning
12.4.3.1.
Capacity Planning
12.4.3.2.
Resource Allocation
12.4.3.3.
Bottleneck Analysis
12.5.
Healthcare Analytics
12.5.1.
Disease Prediction
12.5.1.1.
Risk Factor Analysis
12.5.1.2.
Early Warning Systems
12.5.1.3.
Population Health Management
12.5.2.
Treatment Effectiveness
12.5.2.1.
Outcome Prediction
12.5.2.2.
Personalized Medicine
12.5.2.3.
Clinical Decision Support
12.5.3.
Operational Efficiency
12.5.3.1.
Resource Planning
12.5.3.2.
Patient Flow Optimization
12.5.3.3.
Readmission Prediction
12.6.
Marketing Analytics
12.6.1.
Campaign Optimization
12.6.1.1.
Response Prediction
12.6.1.2.
Channel Attribution
12.6.1.3.
Budget Allocation
12.6.2.
Lead Scoring
12.6.2.1.
Prospect Identification
12.6.2.2.
Conversion Prediction
12.6.2.3.
Sales Pipeline Management
12.6.3.
Market Research
12.6.3.1.
Trend Analysis
12.6.3.2.
Consumer Behavior
12.6.3.3.
Competitive Intelligence
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11. Model Deployment and Production
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13. Ethics and Responsible AI