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Q.9 What MLOps principles Enterprise should consider while building ML-based software apart from Deployment & Monitoring ?1. Versioning2. Testing3. Automation & Reproducibility4. All the above

Question

Q.9 What MLOps principles Enterprise should consider while building ML-based software apart from Deployment & Monitoring ?1. Versioning2. Testing3. Automation & Reproducibility4. All the above

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Solution

The correct answer is 4. All the above.

When building ML-based software, enterprises should consider the following principles apart from Deployment & Monitoring:

  1. Versioning: This involves keeping track of all changes made to both the code and data. It allows for better control and tracking of the model's performance over time.

  2. Testing: This is crucial to ensure the model's accuracy and reliability. It involves evaluating the model's performance using various metrics and techniques.

  3. Automation & Reproducibility: This involves automating as many steps as possible in the ML pipeline to reduce manual errors and increase efficiency. Reproducibility ensures that the model's results can be consistently replicated, which is crucial for debugging and improving the model.

Therefore, all of the above principles are important considerations when building ML-based software.

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