ML basics and ML pipelines
What is ML? ML is a subfield of artificial intelligence (AI) that focuses on building models and algorithms to learn patterns and relationships from data and make predictions or decisions. A typical ML project involves the following process – the so-called ML pipeline:
- Problem framing: Define ML problems from business projects
- Data collection: Collect data from various sources, which may involve data labeling
- Data evaluation: Examine the data using statistical tools
- Feature engineering: Select and extract model features and targets
- Model training: Train the model with the training dataset
- Model verification: Verify the model with the verification dataset
- Model testing: Test the model with the testing dataset
- Model deployment: Deploy the ML model to production
Figure 6.1 shows the ML pipeline, which is an iterative process to collect data and develop ML models for deployment:
Figure...
