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You didn't really describe a stack. Which is fine, because academic research usually doesn't really reuse code ;) A proper ML stack is something like: - Data
by chronic379019 7y ago
You didn't really describe a stack. Which is fine, because academic research usually doesn't really reuse code ;)
A proper ML stack is something like:
- Data format in X schema
- Model trained on Y library/platform
- Evaluated and tested using Z
- Serialized in A format
- Stored on cloud B
- Deployed using C
- Versioned using D
- Real-time monitoring using E