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Natural Language Processing (NLP) 自然语言处理

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

NYUNew York UniversityNLP with Representation LearningN-Gram ModelsAdditive SmoothingInterpolation Smoothing

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

Stevens Institute of TechnologyCS584Natural Language ProcessingDependency ParsingNLPPython

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.

COMP5046 Natural Language Processing - Assignment 1: Predict the length of a Wikipedia article

The University of SydneyCOMP5046COMP4446Natural Language ProcessingBag-of-WordsSGD optimiser

In this assignment, we will explore ways to predict the length of a Wikipedia article based on the first 100 tokens in the article.

CISC7021 - Applied Natural Language Processing - Assignment 1: 𝑛-gram language models

CISC7021Applied Natural Language Processing𝑛-gram language modelsSRILM

In this assignment, we will prepare 𝑛-gram language models and evaluate the test set's perplexity. We will learn how to create a language model using the language model toolkit SRILM

COMP 7607: Natural Language Processing - Assignment 1: N-gram Language Model

COMP 7607COMP7607Natural Language ProcessingN-gram Language ModelPython

Zoie comes from Beijing and she is learning English. She finds it sometimes difficult to decide which preposition she should use in some cases. For example, should she say “they live in a small town” or “they live at a small town”?

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