Evaluating performance: accuracy, precision, recall and F1-score
Channel: Applied Language Technology
Date: 2021-02-23

In this video, I introduce you to basic metrics for evaluating the performance of natural language processing models – accuracy, precision, recall and F1-score – and how they can be calculated using the scikit-learn library for Python.

✨ Check out the learning materials associated with this video: https://applied-language-technology.mooc.fi/html/notebooks/part_ii/05_evaluating_nlp.html#evaluating-the-performance-of-language-models

✨ Clone the repository with Jupyter Notebooks for interactive computing from GitHub: https://github.com/Applied-Language-Technology/notebooks

✨ Check out other videos in the Working with Text in Python playlist: https://youtube.com/playlist?list=PL6cQi6qFlek0rF-aCox3YHOWNdTZSFakA