We explain how to retrieve estimates of a model's performance using scoring metrics, before taking a look at finding and diagnosing the potential problems of a machine learning algorithm.
Synthetic Data and the Data-centric Machine Learning Life Cycle
Maximizing the Potential of Large Language Models
Melody Dunn on LinkedIn: Supply Chain Innovation is a key to success
Doc Mabuse (@DocMabuse7) / X
End To End Guide For Machine Learning Projects - KDnuggets
Choosing Between Model Candidates - KDnuggets
Machine Learning Security - KDnuggets
Finetuning Large Language Models
Training Data Quality: Why It Matters in Machine Learning