Example Tutorials

This chapter provides detailed usage examples of RecIS, covering various application scenarios from basic to advanced.

• Basic Usage
  • Environment Setup
  • Basic Concepts
  • Data Processing
  • Feature Engineering
  • Sparse Embedding Tables
  • Training with Trainer
• DeepFM Example Model
  • Data Construction
  • Data Definition
  • Feature Processing Configuration
  • Embedding Configuration
  • Model Definition
  • Training Deepfm model
• Seq2Seq Example Model
  • Data Construction
  • Data Definition
  • Feature Processing Configuration
  • Embedding Configuration
  • Model Definition
  • Training Entry
• CTR Example Model
  • Data Construction
  • Data Definition
  • Feature Processing Configuration
  • Embedding Configuration
  • Model definition
  • Training
  • Start training

Example Overview

Example List

Example Name	Description
Basic Usage	Basic usage methods of RecIS
DeepFM Example Model	Complete DeepFM model implementation
Seq2Seq Example Model	Complete Seq2Seq model implementation
CTR Example Model	Example CTR model, learn more feature processing patterns

Learning Path Recommendations

Beginner Path

1. Read Project Introduction to understand basic RecIS concepts

2. Follow Quick Start to complete your first model

3. Learn Basic Usage to master basic usage

4. Practice DeepFM Example Model to understand the complete workflow

Advanced User Path

1. Practice Seq2Seq Example Model to understand other training paradigms

2. Practice CTR Example Model to understand more complex data processing workflows

3. Refer to API documentation for custom development

Expert User Path

1. Study source code implementation principles

2. Contribute code and features

3. Optimize performance and extend functionality

4. Share best practices

Common Application Scenarios

Recommendation Systems

• User-item recommendation

• Content recommendation

• Collaborative filtering

• Deep learning recommendation models

Advertising Systems

• CTR prediction

• CVR prediction

• Bid optimization

• Audience targeting

Search Ranking

• Search result ranking

• Query understanding

• Relevance calculation

• Personalized search

Risk Control Systems

• Fraud detection

• Risk assessment

• Anomaly detection

• Credit scoring

Getting Help

If you encounter problems while using the examples:

1. Check Frequently Asked Questions for frequently asked questions

2. Refer to detailed API Documentation API documentation

3. Ask questions in GitHub Issues

4. Join technical discussion groups for support

Contributing Examples

We welcome contributions of new examples and tutorials:

1. Fork the project repository

2. Create new example files

3. Add detailed documentation

4. Submit a Pull Request

Example Contribution Guidelines

• Follow project coding standards

• Provide complete running instructions

• Include necessary comments and documentation

• Verify code correctness and runnability