Анализ неструктурированных данных

2024/2025

Статус: Маго-лего

Кто читает: Международная лаборатория прикладного сетевого анализа

Когда читается: 1, 2 модуль

Охват аудитории: для своего кампуса

Язык: русский

Кредиты: 6

Полная версия программы учебной дисциплины

Аннотация

This course focuses on applied methods and existing tools for information retrieval: web scrap-ing, data preprocessing, natural language processing. All methods considered in this course require basic knowledge of discrete mathematics and probabilistic theory. For instance, most NLP and IR methods use conditional probability. In this course, we show the implementation of contemporary approaches in existing software packages (preferably in the python frameworks), and demonstrate how these methods can be used for the solution of some real-world problems.

Цель освоения дисциплины

to show the implementation of contemporary approaches in existing software packages (preferably in the python frameworks), and demonstrate how these methods can be used for the solution of some real-world problems.

Планируемые результаты обучения

be able to criticize constructively and determine existing issues with applied nlp tasks
be able to get necessary data for research and applied projects
be able to perform basic ETL operations with datasets and unstructured data
have an understanding of the basic principles of information retrieval
have the skill to meaningfully develop an appropriate data analysis pipeline
have the skill to work unstructured text data
know advantages of existing natural language processing packages
know the basic principles behind the the existing deep learning approaches