Code for Precision, Recall and F1-Score | Evaluation Metrics

Code for Precision, Recall and F1-Score | Evaluation Metrics | Classification Problem.

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Are you struggling to understand how to evaluate your machine learning models? In this video, we'll break down the key metrics-Precision, Recall, and F1 Score-that every data scientist needs to know. Whether you're working on a classification problem or optimizing your model for real-world applications, these metrics are crucial for understanding your model's accuracy and effectiveness.
What You’ll Learn:
•⁠ ⁠Precision:How to measure the accuracy of positive predictions.
•⁠ ⁠Recall: Understanding the sensitivity of your model in identifying positive instances.
•⁠ ⁠F1 Score:The perfect balance between Precision and Recall.
•⁠ ⁠Practical examples and real-world applications.
•⁠ ⁠Tips to improve your model's performance using these metrics.
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