NLG focuses on generating natural language from structured data while NLP focuses on understanding and processing natural language.
Both NLG and NLP are crucial for enabling machines to interact with humans in a natural way.
There are several types of NLG, including template-based, rule-based, and machine learning-based NLG.
Each type of NLG has its own strengths and weaknesses, and choosing the right type depends on the specific use case.
NLG is used in various industries such as finance, healthcare, and e-commerce to generate reports, summaries, and personalized messages.
NLG has proven to be a game-changer in many industries, enabling businesses to save time and money while improving customer satisfaction.
NLG can help businesses streamline their operations, improve customer communication, and reduce costs.
In personal projects, NLG can help automate repetitive tasks, generate personalized content, and enhance creativity.