MOURI Tech Implementation Process for Machine Learning
Business Objective Definition
Align machine learning models with clearly defined business KPIs and measurable outcomes.
Data Collection & Preparation
Perform data cleansing, normalization, enrichment, and quality checks to ensure model reliability.
Feature Engineering
Create domain-driven features that improve model accuracy and interpretability.
Model Training & Validation
Develop and validate regression, classification, and ensemble models using real-world datasets.
Deployment & Monitoring
Deploy models via APIs or batch pipelines with continuous performance tracking and governance controls.