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Explores the evaluation of natural language generation models, emphasizing the importance of human judgments and the limitations of content overlap metrics.
Introduces Natural Language Processing, covering text preprocessing, sentiment analysis, and topic analysis, with a focus on building a climate change risk index.
Delves into digitizing historical documents, standardizing document structure, and applying neural networks for text recognition and image segmentation.
Explores the aim and process of batch normalization in deep neural networks, emphasizing its importance in stabilizing mean input and solving the vanishing gradient problem.
