Applied machine learning
Selecting and integrating models around a defined product need, with attention to data quality, evaluation, latency, and operating cost.
Explore this topic05 / Artificial intelligenceKAWINDU WIJEWARDHANE
Models are only useful inside systems.
Artificial intelligence work grounded in software delivery: define the problem, test the model, integrate it carefully, and measure how it performs in use.
From model capability to operating product.
The engineering around a model determines whether an AI feature remains useful after the demonstration.
Language systems
Natural-language processing for classification, extraction, search, and workflow automation where the output can be reviewed and measured.
Explore this topicReliable integration
Building the APIs, queues, observability, fallbacks, and human controls required to run model-assisted features inside dependable software.
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