What is AI Model Development?
AI model development is the end-to-end process of designing, training, evaluating, and deploying artificial intelligence systems that can learn patterns from data to perform tasks such as prediction, classification, or decision-making—without being explicitly programmed.
AI Model Development Lifecycle: 7 Key Stages
- Problem Definition
Define the objective, use case, and success metrics for the AI solution. - Data Collection
Gather relevant and high-quality data from multiple sources. - Data Preparation
Clean, label, structure, and split the data for training and evaluation.
- Model Selection & Training
Choose appropriate algorithms or architectures and train the model using training data. - Model Evaluation
Test the model on validation/test data using metrics like accuracy, F1-score, or MAE. - Deployment
Integrate the trained model into production environments (cloud, mobile, edge). - Monitoring & Maintenance
Track model performance, detect data/model drift, and update or retrain as needed.