Machine Learning Implementation
Machine learning implementation
Build or adapt machine learning when the problem needs a model — predictive analytics, computer vision, or NLP.
A useful inquiry names the data you already have, the decision the model should support, and the constraint.
We define evaluation criteria around your data and the decisions the model needs to support.
Strategy and implementation can be one engagement if you say so up front.
Questions about Machine Learning Implementation
What is needed before a machine learning project starts?
Identify the available data, the decision the model should support, and the constraints. Sanritech defines evaluation criteria around the data and the intended decision, including predictive analytics, computer vision, or natural language processing.