Limitations in NLP focuses on the challenges and constraints faced in natural language processing systems when handling human language data. It highlights issues such as ambiguity, sarcasm detection, contextual understanding, and language variability. This training explains how NLP models struggle with low-resource languages, domain adaptation, and bias in training data. It also covers limitations in sentiment analysis accuracy, entity recognition, and real-time language processing. You will learn how these challenges impact real-world applications like chatbots, translation systems, and text analytics. The course also discusses strategies and best practices to improve NLP model performance and reliability.
Showing the single result
