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ML engineering pipelines

Feature prep, batch inference, model-serving hooks, and production ML workflow glue.

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ML engineering pipelines easy

How to Evaluate Accuracy, Precision, and Recall in Python

Compute accuracy, precision, and recall for a binary classification model using scikit-learn's metrics functions.

metrics classification scikit-learn
Python 
from sklearn.metrics import accuracy_score, precision_score, recall_score

if __name__ == "__main__":
    y_true = [0, 1, 1, 0, 1, 0, 1, 1]
    y_pred = [0, 1, 0, 0, 1, 0, 1, 1]

    accuracy = accuracy_score(y_true, y_pred)
    precision = precision_score(y_true, y_pred)
    recall = recall_score(y_true, y_pred)

   …
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