Understand language acquisition
The purpose of the [course_title] is to show you the natural process of language learning. You will learn the study of human language from a computational perspective. The course covers the major areas of language learning processes such as:
- syntactic – the study of the structure of the sentence
- Semantic – the study of meaning
- discourse analysis – study to analyse written, vocal, or sign language use
- corpus-based methods or Corpus linguistics – the study of language as expressed in corpora (samples) of “real world” text.
In short, the [course_title] covers all the major methods and models in syntactic parsing, information extraction, statistical machine translation, dialogue systems, and summarisation.
This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer need to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.
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Course Credit: MIT
|Introduction and Overview||00:26:00|
|Parsing and Syntax I||00:22:00|
|Smoothed Estimation, and Language Modeling||00:23:00|
|Parsing and Syntax II||00:28:00|
|The EM Algorithm||00:27:00|
|The EM Algorithm Part II||00:26:00|
|Lexical Similarity (cont.)||00:22:00|
|Tagging and History-based Models||00:23:00|
|Computational Modeling of Discourse||00:21:00|
|Local Coherence and Coreference||00:21:00|
|Machine Translation (cont.)||00:26:00|
|Machine Translation (cont.) 2||00:23:00|
|Courtesy of Philipp Koehn and Ivona Kucerova. Used with permission||00:23:00|
|Graph-based Methods for NLP Applications||00:26:00|
|Word Sense Disambiguation||00:29:00|
|Global Linear Models||00:23:00|
|Global Linear Models Part II||00:26:00|
|Dialogue Processing (cont.)||00:24:00|
|Submit Your Assignment||00:00:00|
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