Tokenization and text preparation
Learn how tokenization, normalization and text cleaning prepare data for analysis. Explore lexical patterns and regular expressions, and consider which transformations fit your task.
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Practical explanations of the techniques behind text applications
Sentiment analysis and text classification
Explore how classifiers estimate sentiment in text. Compare supervised approaches, embeddings and evaluation metrics, with examples such as feedback and customer reviews.
Learn moreChatbot architecture and conversational systems
Understand intent recognition, conversation state and response generation. Follow how these components work together and where fallback handling or human support is needed.
Learn moreLanguage models: ideas and applications
Explore embeddings, attention and Transformers, then consider when adapting a pretrained model is useful. Connect the architecture with its data and evaluation requirements.
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