Simplified Explanation
1.Define Business Value: What are the business values that the AI project must deliver?
2.Collect Relevant Data: All business data collected from databases, processes, activities, reports, all business documents, customer data, business emails, rules and regulations, operational data, etc.
3.Data Processing and Cleaning: Verification and Validation of all collected data.
4.Mathematical Transformation: Using Python language to transform data using math.
5.Train AI Model: It is making machines to learn based on mathematically transformed data to create AI engines known as ML Models.
6.Evaluate AI Model: Ensuring the ML Model is accurate, and useable based on use cases.
7.Optimize and Tune AI Model: Fine-Tune AI Model.
8.Deploy AI Model for Use: Productionize the AI Model (application) and maintain it.
