Build, deploy, and scale a production-ready AI text classification API with Python and FastAPI—training, serving, security, metrics, and monitoring.
A practical blueprint of safety patterns, architecture, and policies to keep agentic AI reliable, secure, and aligned in production.
Hands-on knowledge distillation tutorial for compact models: concepts, PyTorch/Keras code, tuning tips, and deployment with quantization.
Design and implement a low-latency real-time AI translation API: architecture, protocols, latency budgets, security, and production-ready code examples.
A practical guide to integrating TensorFlow Lite models into Flutter for fast, private, offline on-device AI with performance tuning and code examples.
Practical guide to AI fraud detection API integration: architecture, payloads, security, thresholds, MLOps, and operations with code samples.
