课程信息
4.1
1,014 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....
Globe

100% 在线课程

立即开始,按照自己的计划学习。
Calendar

可灵活调整截止日期

根据您的日程表重置截止日期。
Intermediate Level

中级

Clock

建议:8 hours/week

完成时间大约为17 小时
Comment Dots

English

字幕:English

您将学到的内容有

  • 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

您将获得的技能

Text MiningNatural Language ToolkitNatural Language ProcessingPython Programming
Globe

100% 在线课程

立即开始,按照自己的计划学习。
Calendar

可灵活调整截止日期

根据您的日程表重置截止日期。
Intermediate Level

中级

Clock

建议:8 hours/week

完成时间大约为17 小时
Comment Dots

English

字幕:English

教学大纲 - 您将从这门课程中学到什么

1

章节
Clock
完成时间为 8 小时

Module 1: Working with Text in Python

...
Reading
5 个视频(共 56 分钟), 4 个阅读材料, 3 个测验
Video5 个视频
Handling Text in Python18分钟
Regular Expressions16分钟
Demonstration: Regex with Pandas and Named Groups5分钟
Internationalization and Issues with Non-ASCII Characters12分钟
Reading4 个阅读材料
Course Syllabus10分钟
Help us learn more about you!10分钟
Notice for Auditing Learners: Assignment Submission10分钟
Resources: Common issues with free text10分钟
Quiz2 个练习
Practice Quiz8分钟
Module 1 Quiz12分钟

2

章节
Clock
完成时间为 6 小时

Module 2: Basic Natural Language Processing

...
Reading
3 个视频(共 36 分钟), 3 个测验
Video3 个视频
Basic NLP tasks with NLTK16分钟
Advanced NLP tasks with NLTK16分钟
Quiz2 个练习
Practice Quiz4分钟
Module 2 Quiz10分钟

3

章节
Clock
完成时间为 7 小时

Module 3: Classification of Text

...
Reading
7 个视频(共 94 分钟), 2 个测验
Video7 个视频
Identifying Features from Text8分钟
Naive Bayes Classifiers19分钟
Naive Bayes Variations4分钟
Support Vector Machines24分钟
Learning Text Classifiers in Python15分钟
Demonstration: Case Study - Sentiment Analysis9分钟
Quiz1 个练习
Module 3 Quiz14分钟

4

章节
Clock
完成时间为 6 小时

Module 4: Topic Modeling

...
Reading
4 个视频(共 58 分钟), 2 个阅读材料, 3 个测验
Video4 个视频
Topic Modeling8分钟
Generative Models and LDA13分钟
Information Extraction18分钟
Reading2 个阅读材料
Additional Resources & Readings10分钟
Post-Course Survey10分钟
Quiz2 个练习
Practice Quiz4分钟
Module 4 Quiz10分钟
4.1
Direction Signs

20%

完成这些课程后已开始新的职业生涯
Briefcase

83%

通过此课程获得实实在在的工作福利
Money

10%

加薪或升职

热门审阅

创建者 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!

创建者 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.

讲师

V. G. Vinod Vydiswaran

Assistant Professor
School of Information

关于 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....

关于 Applied Data Science with Python 专项课程

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

常见问题

  • 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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