課程信息
4.1
1,100 ratings
215 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% 在線課程

立即開始,按照自己的計劃學習。
Calendar

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Intermediate Level

中級

Clock

建議:8 hours/week

完成時間大約為17 小時
Comment Dots

English

字幕:English

您將學到的內容有

  • 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

您將獲得的技能

Natural Language Toolkit (NLTK)Text MiningPython ProgrammingNatural Language Processing
Globe

100% 在線課程

立即開始,按照自己的計劃學習。
Calendar

可靈活調整截止日期

根據您的日程表重置截止日期。
Intermediate Level

中級

Clock

建議:8 hours/week

完成時間大約為17 小時
Comment Dots

English

字幕:English

教學大綱 - 您將從這門課程中學到什麼

1

章節
Clock
完成時間為 8 小時

Module 1: Working with Text in Python

...
Reading
5 個視頻(共 56 分鐘), 4 個閱讀材料, 3 個測驗
Video5 個視頻
Handling Text in Python18分鐘
Regular Expressions16分鐘
Demonstration: Regex with Pandas and Named Groups5分鐘
Internationalization and Issues with Non-ASCII Characters12分鐘
Reading4 個閱讀材料
Course Syllabus10分鐘
Help us learn more about you!10分鐘
Notice for Auditing Learners: Assignment Submission10分鐘
Resources: Common issues with free text10分鐘
Quiz2 個練習
Practice Quiz8分鐘
Module 1 Quiz12分鐘

2

章節
Clock
完成時間為 6 小時

Module 2: Basic Natural Language Processing

...
Reading
3 個視頻(共 36 分鐘), 3 個測驗
Video3 個視頻
Basic NLP tasks with NLTK16分鐘
Advanced NLP tasks with NLTK16分鐘
Quiz2 個練習
Practice Quiz4分鐘
Module 2 Quiz10分鐘

3

章節
Clock
完成時間為 7 小時

Module 3: Classification of Text

...
Reading
7 個視頻(共 94 分鐘), 2 個測驗
Video7 個視頻
Identifying Features from Text8分鐘
Naive Bayes Classifiers19分鐘
Naive Bayes Variations4分鐘
Support Vector Machines24分鐘
Learning Text Classifiers in Python15分鐘
Demonstration: Case Study - Sentiment Analysis9分鐘
Quiz1 個練習
Module 3 Quiz14分鐘

4

章節
Clock
完成時間為 6 小時

Module 4: Topic Modeling

...
Reading
4 個視頻(共 58 分鐘), 2 個閱讀材料, 3 個測驗
Video4 個視頻
Topic Modeling8分鐘
Generative Models and LDA13分鐘
Information Extraction18分鐘
Reading2 個閱讀材料
Additional Resources & Readings10分鐘
Post-Course Survey10分鐘
Quiz2 個練習
Practice Quiz4分鐘
Module 4 Quiz10分鐘
4.1
Direction Signs

20%

完成這些課程後已開始新的職業生涯
Briefcase

83%

通過此課程獲得實實在在的工作福利
Money

10%

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創建者 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!

創建者 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.

講師

V. G. Vinod Vydiswaran

Assistant Professor
School of Information

關於 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....

關於 Applied Data Science with Python 專項課程

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 a basic 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

常見問題

  • 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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