Software Development Life Cycle of Machine Learning Projects

Software Development Life Cycle of Machine Learning Projects is split into two phases:

R&D: Preprocessing: Business objective and rules R&D: BPM. UML. Use Case. etc.

Data R&D. Data Profiling. ETL: Extraction. Cleanup. Integration. Transformation. Aggregation.
Solution Model R&D: Understand the problem and the solution required (Classification, number forecasting, etc.) Use different techniques, get the most accurate one.

Operational: This is smaller lifecycle.

  1. Training / Incremental Training.
  2. Testing.
  3. Production.

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