Being able to round a DateTime object in Pandas to the nearest hour can be extremely helpful for feature engineering. In this post, I will walk through how to do this simply in multiple variations.
Clustering is a common unsupervised learning approach, but it can be difficult to know which the best evaluation metrics are to measure performance. In this post, I explain why we need to consider different metrics, and which is best to choose.
MAPE (Mean Absolute Percentage Error) is a common regression machine learning metric, but when the actual values are close to 0 it becomes undefined. In this post, I explain why this happens and what to do when it does.
MAE (Mean Absolute Error) is a popular metric to use for regression machine learning models, but what is a good score? In this post, I explain what MAE is, what a good value is, and answer some common questions.
MAE is a common regression machine learning metric, but it can be confusing to know how to interpret the values. In this post, I explain what MAE is, how to interpret the values and walk through an example.