# Data Classification

Once data is embedded, a classification algorithm, such as a neural network or a logistic regression model, can be trained on these embeddings to classify the data into different categories. The advantage of using embeddings is that they capture underlying relationships and similarities between data points, even if the raw data is complex or high-dimensional, improving classification accuracy in tasks like text classification, image categorization, and recommendation systems.

Learn more from the following resources:

- [@video@Text Embeddings, Classification, and Semantic Search (w/ Python Code)](https://www.youtube.com/watch?v=sNa_uiqSlJo)