#A.I. Deep learning neural network models used for predictive modeling may need to be updated. This may be because the data has changed since the model was developed and deployed, or it may be the case that additional labeled data has been made ava...

#A.I. Optimization involves finding the inputs to an objective function that result in the minimum or maximum output of the function. The open-source Python library for scientific computing called SciPy provides a suite of optimization algorithms. ...

#A.I. Semi-supervised learning refers to algorithms that attempt to make use of both labeled and unlabeled training data. Semi-supervised learning algorithms are unlike supervised learning algorithms that are only able to learn from labeled trainin...

#A.I. Gradient boosting is an ensemble of decision trees algorithms. It may be one of the most popular techniques for structured (tabular) classification and regression predictive modeling problems given that it performs so well across a wide range...

#A.I. Occam’s razor suggests that in machine learning, we should prefer simpler models with fewer coefficients over complex models like ensembles. Taken at face value, the razor is a heuristic that suggests more complex hypotheses make more assumpt...