Explores document retrieval, classification, sentiment analysis, TF-IDF matrices, nearest-neighbor methods, matrix factorization, regularization, LDA, contextualized word vectors, and BERT.
Explores the evaluation of natural language generation models, emphasizing the importance of human judgments and the limitations of content overlap metrics.
Discusses the ethical implications of NLP systems, focusing on biases, toxicity, and privacy concerns in language models.
Covers modern Neural Network approaches to NLP, focusing on word embeddings, Neural Networks for NLP tasks, and future Transfer Learning techniques.
