1. Recap
Congratulations! We have now covered how to train and test a text classification model from end to end!
2. Recap
We used window function SQL to process sequential data.
We used it to extract useful data from a train schedule timetable, and to surface frequent word sequences from raw text.
We transformed that data to obtain feature data for training a machine learning text classification model.
We selected subsets of that feature data to create a training set and and a evaluation set.
We trained a classification model,
We used the trained model for prediction,
And evaluated it on a test set.
3. Congratulations!
Thank you for your time and attention. You might practice some of these techniques using the dataset provided here, or, apply these techniques you just learned to a different dataset. You might tackle a project. Thanks again for joining, and congratulations on completing the course!