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Natural Language Processing (NLP) 自然语言处理

Natural Language Processing (NLP) 自然语言处理

CISC3025 Natural Language Processing Project 3: Maximum entropy model

Natural Language ProcessingNLP自然语言处理

In this project, you will be building a maximum entropy model (MEM) for identifying person names in newswire texts (Label=PERSON or Label=O)

Natural Language Engineering: Assessed Coursework: Classification

Natural Language ProcessingNLP自然语言处理

Design and carry out an experiment into the impact of the length of the wordlists on the wordlist classifier. Make sure you describe design decisions in your experiment, include a graph of your results and discuss your conclusions.

EECS595: Natural Language Processing Homework 4: Probabilistic Context Free Grammar and Dependency Parsing

Natural Language ProcessingNLP自然语言处理

This exercise is to get you familiar with dependency parsing and the Stanford CoreNLP [1] toolkit. You may also need to consult the inventory of universal dependency relations. You have two options to complete this exercise.

EECS595: Natural Language Processing Homework 4: Probabilistic Context Free Grammar and Dependency Parsing

Natural Language ProcessingNLP自然语言处理

This exercise is to get you familiar with dependency parsing and the Stanford CoreNLP [1] toolkit. You may also need to consult the inventory of universal dependency relations. You have two options to complete this exercise.

COMP SCI 7417 Applied Natural Language Processing - Assignment - Classifier and Distributional Semantics

Natural Language ProcessingNLP自然语言处理

In this question, you will be investigating the distributional hypothesis: words which appear in similar contexts tend to have similar meanings.

[2021] CS3002 Artificial Intelligence - Final Exam - Q7: Deep Learning for Natural Language Processing

Natural Language ProcessingNLP自然语言处理

This question is part of the CS3002 Artificial Intelligence, final exam May 2021, Brunel University London

Word Representation in Biomedical Domain

Natural Language ProcessingNLP自然语言处理

BERT introduces a new language model for pre-training named Masked Language Model (MLM). The advantage of MLM is that the word representations by MLM will be contextualised.

HDAG Interview Take Home Assignment - Data Analytics

Natural Language ProcessingNLP自然语言处理

This take-home assignment is meant to evaluate your background and fit for a role within HDAG.

NLP with Representation Learning, Fall 2022 - Homework 1: N-Gram Models, Additive Smoothing, Interpolation Smoothing, Backoff and Neural Networks

Natural Language ProcessingNLP自然语言处理

In this section, you will implement a basic n-gram model with no smoothing. The core challenge in doing this is counting the number of occurrences of different n-grams in the training data.

CS584: Natural Language Processing - Assignment 5: Dependency Parsing

Natural Language ProcessingNLP自然语言处理

Given a sentence “I parsed this sentence correctly” with the transitions, complete the following table. The first three steps are provided in the table, showing the configuration of the stack and buffer, as well as the transition and the new dependency (if has) for the following steps.

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