The ML project lifecycle:
- Scoping
- Define project
- Data
- Define data and establish baseline
- Label and organize data
- Modeling
- Select and train model
- Perform error analysis
- Deployment
- Deploy in production
- Monitor & maintain system
有时需要不读重复步骤2，3，4
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