Introduces Natural Language Processing (NLP) and its applications, covering tokenization, machine learning, sentiment analysis, and Swiss NLP applications.
Explores the analysis of mood expressed on Twitter using longitudinal data and text analysis tools, emphasizing the importance of considering biased data.
Provides an overview of Natural Language Processing, focusing on transformers, tokenization, and self-attention mechanisms for effective language analysis and synthesis.
Introduces Natural Language Processing, covering text preprocessing, sentiment analysis, and topic analysis, with a focus on building a climate change risk index.