Machine Learning Series – Part 3: We continue our machine learning discussion, and focus on problems associated with overfitting data, as well as controlling model complexity, a model evaluation and errors introduction, model validation and tuning, and improving model performance.
Machine Learning Series – Part 1: Machine learning is a hot topic for many key reasons, automatically obtain deep insights, recognize unknown patterns, and create high performing predictive models from data, all without requiring explicit programming instructions.
Machine Learning Series – Part 2: We will introduce model performance concepts and then focus on the following parts of the machine learning process: data selection, preprocessing, feature selection, model selection, and model tradeoff considerations.
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