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.
A step-by-step LoRA fine-tuning guide with theory, setup, classic LoRA and QLoRA code, evaluation, merging, and practical tips.
