Об этом курсе
4.1
1,016 ratings
201 reviews
This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text. The second week focuses on common manipulation needs, including regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processes. The third week will apply basic natural language processing methods to text, and demonstrate how text classification is accomplished. The final week will explore more advanced methods for detecting the topics in documents and grouping them by similarity (topic modelling). This course should be taken after: Introduction to Data Science in Python, Applied Plotting, Charting & Data Representation in Python, and Applied Machine Learning in Python....
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Intermediate Level

Промежуточный уровень

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Предполагаемая нагрузка: 8 hours/week

Прибл. 17 ч. на завершение
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English

Субтитры: English

Чему вы научитесь

  • Check
    Apply basic natural language processing methods
  • Check
    Describe the nltk framework for manipulating text
  • Check
    Understand how text is handled in Python
  • Check
    Write code that groups documents by topic

Приобретаемые навыки

Text MiningNatural Language ToolkitNatural Language ProcessingPython Programming
Globe

Только онлайн-курсы

Начните сейчас и учитесь по собственному графику.
Calendar

Гибкие сроки

Назначьте сроки сдачи в соответствии со своим графиком.
Intermediate Level

Промежуточный уровень

Clock

Предполагаемая нагрузка: 8 hours/week

Прибл. 17 ч. на завершение
Comment Dots

English

Субтитры: English

Программа курса: что вы изучите

1

Раздел
Clock
8 ч. на завершение

Module 1: Working with Text in Python

...
Reading
5 видео (всего 56 мин.), 4 материалов для самостоятельного изучения, 3 тестов
Video5 видео
Handling Text in Python18мин
Regular Expressions16мин
Demonstration: Regex with Pandas and Named Groups5мин
Internationalization and Issues with Non-ASCII Characters12мин
Reading4 материала для самостоятельного изучения
Course Syllabus10мин
Help us learn more about you!10мин
Notice for Auditing Learners: Assignment Submission10мин
Resources: Common issues with free text10мин
Quiz2 практического упражнения
Practice Quiz8мин
Module 1 Quiz12мин

2

Раздел
Clock
6 ч. на завершение

Module 2: Basic Natural Language Processing

...
Reading
3 видео (всего 36 мин.), 3 тестов
Video3 видео
Basic NLP tasks with NLTK16мин
Advanced NLP tasks with NLTK16мин
Quiz2 практического упражнения
Practice Quiz4мин
Module 2 Quiz10мин

3

Раздел
Clock
7 ч. на завершение

Module 3: Classification of Text

...
Reading
7 видео (всего 94 мин.), 2 тестов
Video7 видео
Identifying Features from Text8мин
Naive Bayes Classifiers19мин
Naive Bayes Variations4мин
Support Vector Machines24мин
Learning Text Classifiers in Python15мин
Demonstration: Case Study - Sentiment Analysis9мин
Quiz1 практическое упражнение
Module 3 Quiz14мин

4

Раздел
Clock
6 ч. на завершение

Module 4: Topic Modeling

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Reading
4 видео (всего 58 мин.), 2 материалов для самостоятельного изучения, 3 тестов
Video4 видео
Topic Modeling8мин
Generative Models and LDA13мин
Information Extraction18мин
Reading2 материала для самостоятельного изучения
Additional Resources & Readings10мин
Post-Course Survey10мин
Quiz2 практического упражнения
Practice Quiz4мин
Module 4 Quiz10мин
4.1
Direction Signs

20%

начал новую карьеру, пройдя эти курсы
Briefcase

83%

получил значимые преимущества в карьере благодаря этому курсу
Money

10%

стал больше зарабатывать или получил повышение

Лучшие рецензии

автор: CCAug 27th 2017

Quite challenging but also quite a sense of accomplishment when you finish the course. I learned a lot and think this was the course I preferred of the entire specialization. I highly recommend it!

автор: BKJun 26th 2018

Would love to see these courses have more practice questions in each weeks lesson. Would be helpful for repetition sake, and learning vs only doing each question once in the assignments.

Преподаватель

V. G. Vinod Vydiswaran

Assistant Professor
School of Information

О University of Michigan

The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future....

О специализации ''Applied Data Science with Python'

The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have basic a python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data. Introduction to Data Science in Python (course 1), Applied Plotting, Charting & Data Representation in Python (course 2), and Applied Machine Learning in Python (course 3) should be taken in order and prior to any other course in the specialization. After completing those, courses 4 and 5 can be taken in any order. All 5 are required to earn a certificate....
Applied Data Science with Python

Часто задаваемые вопросы

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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