4 steps in building effective machine learning models Building machine learning models that have the ability to generalize well on future data requires thoughtful consideration of the data at hand and of assumptions about various available training algorithms. Ultimate evaluation of a machine learning model’s quality requires an appropriate selection and interpretation of assessment criteria.
Machine learning consists of algorithms that can automate analytical model building. Using algorithms that iteratively learn from data, machine learning models facilitate computers to find hidden insights from Big Data…
