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Artificial Intelligence & Machine Learning · Module 10 of 10

Deploying AI and responsible AI

Ship models and use AI ethically.

📖 Key ideas

  1. Save models (joblib, pickle, ONNX) and serve with FastAPI/Flask.
  2. Build demos with Streamlit or Gradio.
  3. Monitor data drift and accuracy after deployment.
  4. Responsible AI: fairness, transparency, privacy, safety.
  5. Careers: ML engineer, data scientist, AI engineer; certifications from Google, AWS, Microsoft.
💡 Real-life example: Deploying a model is opening the shop; responsible AI is running it honestly and fairly.
Model servingExposing a model via an API
Data driftInput data changing over time
BiasUnfair outcomes for groups
ExplainabilityUnderstanding model decisions