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An announcement for the CS 540 Introduction to Artificial Intelligence course at the University of Wisconsin-Madison for the Fall 2022 semester. The document covers topics related to Natural Language Processing (NLP), including language models, classic NLP tasks, word representations, and training issues. The document also briefly discusses the history of NLP and the progress made in the field. The document could be useful as study notes or a summary for a student preparing for an exam in an NLP-related course.
Typology: Study notes
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University of Wisconsin-Madison Fall 2022
Announcements
Why is it hard? Many reasons:
Approaches to NLP A brief history
Language Models
Training The Model Recall the chain rule
k=0: Uni gram Model
k=1: Bi gram Model
n- gram Training Issues:
For issue 2 , back-off methods
Evaluating Language Models How do we know we’ve done a good job?
Intrinsic Evaluation: Perplexity Perplexity is a measure of uncertainty Lower is better! Examples:
Further NLP Tasks Language modeling is not the only task. Two further types:
1. Auxilliary tasks: - Part-of-speech tagging, parsing, etc. 2. Direct tasks: - Question-answering, translation, summarization, classification (e.g., sentiment analysis)