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.
- Training / Incremental Training.