Efficient Machine Learning: Practical Techniques for Sustainable Models — Pruning, Quantization, Distillation & Deployment
Making machine learning models efficient and sustainable is a priority for teams building real-world systems. Resource constraints, latency targets, and environmental impact push developers to adopt strategies that reduce compute and memory without sacrificing accuracy. Below are practical techniques and design patterns that accelerate deployment and lower operational costs. Why efficiency mattersEfficient models run faster, […]