Careful cross-validation of algorithmic results to ensure accuracy, reliability, and organizational value is being delivered
Mean Squared Error, AUC, ROC, Precision and Recall, Confusion Matrix, F1 Score
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Case Studies
Quantifying Commodity Sentiment with AI
In this case study, Mosaic fine-tuned language models to analyze text and quantify public sentiment to explain commodity pricing with AI. Our team used sentiment model outputs to extract insights regarding price trends for a specific commodity and predict future price movements.
