Predictive Analytics with TensorFlow 6.1: NLP Analytics Pipelines

The video tutorial introduces NLP analytics pipelines, highlighting the workflow from data ingestion to predictive analytics. It emphasizes the importance of feature engineering for unstructured text and discusses challenges faced by MLP models in interpreting semantics. The tutorial explores text analytics techniques like sentiment analysis, topic modeling, TF-IDF, named entity recognition, and event extraction, illustrating their applications in uncovering patterns and relationships in text data.

Explain the concept of named entity recognition and its significance in text analytics.

What is the purpose of event extraction in the context of text analytics?