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学生对 University of Illinois Urbana-Champaign 提供的 Text Mining and Analytics 的评价和反馈

4.5
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735 个评分

课程概述

This course will cover the major techniques for mining and analyzing text data to discover interesting patterns, extract useful knowledge, and support decision making, with an emphasis on statistical approaches that can be generally applied to arbitrary text data in any natural language with no or minimum human effort. Detailed analysis of text data requires understanding of natural language text, which is known to be a difficult task for computers. However, a number of statistical approaches have been shown to work well for the "shallow" but robust analysis of text data for pattern finding and knowledge discovery. You will learn the basic concepts, principles, and major algorithms in text mining and their potential applications....

热门审阅

WP

Aug 22, 2017

Most of the lessons are mathematical formulae in which, in my opinion, I need more real case study/practice to make myself clearly understand on how do those formulae perform.

MR

Jul 22, 2017

The workflow is clear and the professor speaks to the students directly about all aspects without skimming the material.

筛选依据：

76 - Text Mining and Analytics 的 100 个评论（共 148 个）

创建者 Gourav A

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Oct 26, 2018

Excellent course.

创建者 RAM K

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Aug 23, 2020

excellent course

创建者 aditya r

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Dec 12, 2020

its nice course

创建者 Raja R

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Jan 22, 2021

Great Course!

创建者 VIKAS M

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Dec 16, 2020

fun learning

创建者 Manikant R

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Jun 21, 2020

great course

创建者 David O

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Jul 1, 2018

Great course

创建者 KATKURI G K R

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Aug 31, 2023

good course

创建者 黄莉婷

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Dec 26, 2017

讲的很不错，受益匪浅。

创建者 Florov M

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Apr 3, 2020

Excellent!

创建者 Kamlesh C

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Aug 22, 2020

Thank you

创建者 Kumar B P

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May 8, 2020

Excellent

创建者 Assoc.Prof., C V T C

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Apr 29, 2020

excellent

创建者 MItrajyoti K

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Oct 23, 2019

Very good

创建者 2K18/SE/129 V K

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May 9, 2022

good one

创建者 Hernán C V

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May 4, 2017

Awesome!

创建者 Arefeh Y

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Nov 4, 2016

Great!!

创建者 kalashri

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Aug 23, 2023

great

创建者 Нұрсұлтан У

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Feb 6, 2025

++++

创建者 Swapna.C

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Jul 17, 2020

nice

创建者 Mrinal G

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May 20, 2019

Nice

创建者 Isaiah M

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Jan 2, 2018

T

创建者 Valerie P

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Jul 11, 2017

E

创建者 Deepak S

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Aug 11, 2016

E

创建者 Jennifer K

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Jul 5, 2017

Despite the amount of material to cover, this course did a great job of introducing the right amount of detail for various aspects (motivation, algorithms, algorithmic reasoning, evaluation) on topic modelling, text clustering, text categorization, sentiment analysis, aspect sentiment analysis, evaluation of text and non-text data in context, and more. Definitely read the additional resources for the material - it will give you an incredibly in-depth view to what you learned in the lectures and also give you a start on implementing the covered algorithms on your own.

The only thing I missed in this class are assignments for implementing the algorithms in a language other than C++ and in a framework other than MeTA. It would make sense to provide this opportunity in additional, commonly-used data-science languages such as Python!