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Building an AI Application from Scratch

Knowledge Tree

AI engineer

Iceberg Model

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1. AI Code Review Robot

2. Identifying the Goal and Analyzing Requirements

  • Goal Definition

  • User Groups

  • Requirements

3. Data Collection and Preparation

  • Data Sources

  • Preprocessing Steps

4. Selecting Technology

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Model Development

  1. Choose a Pre-trained Model
  2. Fine-tune the Model

5. System Integration and Deployment

System Architecture

  • Frontend
  • Backend
  • Database

Integration

Deployment

6. Monitoring and Continuous Optimization

Monitoring

  • Real-time logging to identify failures and bottlenecks.
  • Metrics:
  • Response time.
  • Accuracy of suggestions.

Continuous Improvement

  • Regular updates to the model with new data.
  • Expand support for more programming languages.
  • Collect user feedback for better recommendations.

7. Key Takeaways

  • Split code into smaller chunks.
  • Add line numbers to code snippets.
  • Twice review
  • First for review code
  • Second for review comments validation
  • Use reviewdog helps to summit the comments to the PR.

8. Cost

9. Closing Thoughts

What will AI change in the future?