Removing unimportant weights or connections that contribute minimally to the model's output.
Communication in India is high-context , meaning that relationships and non-verbal cues are just as important as words. Business and social interactions are built on long-term trust rather than just transactional agreements. Sustainability and Diversity Designing Machine Learning Systems By Chip Huyen Pdf
[ Data Engineering ] ──> [ Model Development ] ──> [ Deployment & Serving ] ──> [ Monitoring & Continuity ] ▲ │ └─────────────────────────────── Feedback Loop ───────────────────────────────────┘ Data Engineering and Feature Stores Sustainability and Diversity [ Data Engineering ] ──>
Latency, throughput, uptime, and resource consumption. She explains how to implement continuous monitoring to
A model is not a "fire-and-forget" artifact; it is a living system. In this chapter, Huyen provides a playbook for the post-deployment world. She explains how to implement continuous monitoring to detect data drift (changes in input data) and concept drift (changes in the relationship between input and output), how to set up prediction serving, and how to establish feedback loops for continuous learning. This final piece of the puzzle turns a static model into a dynamic, adaptive system that improves over time.
Techniques for acquiring high-quality labels at scale.
Before algorithms, you need data. The book highlights the importance of: Identifying and fixing data bottlenecks.