À propos de ce cours
4.1
1,010 ratings
200 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

Niveau intermédiaire

Clock

Recommandé : 8 hours/week

Approx. 17 heures pour terminer
Comment Dots

English

Sous-titres : English

Ce que vous allez apprendre

  • 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

Compétences que vous acquerrez

Text MiningNatural Language ToolkitNatural Language ProcessingPython Programming
Globe

Cours en ligne à 100 %

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Calendar

Dates limites flexibles

Réinitialisez les dates limites selon votre disponibilité.
Intermediate Level

Niveau intermédiaire

Clock

Recommandé : 8 hours/week

Approx. 17 heures pour terminer
Comment Dots

English

Sous-titres : English

Programme du cours : ce que vous apprendrez dans ce cours

1

Section
Clock
8 heures pour terminer

Module 1: Working with Text in Python

...
Reading
5 vidéos (Total 56 min), 4 lectures, 3 quiz
Video5 vidéos
Handling Text in Python18 min
Regular Expressions16 min
Demonstration: Regex with Pandas and Named Groups5 min
Internationalization and Issues with Non-ASCII Characters12 min
Reading4 lectures
Course Syllabus10 min
Help us learn more about you!10 min
Notice for Auditing Learners: Assignment Submission10 min
Resources: Common issues with free text10 min
Quiz2 exercices pour s'entraîner
Practice Quiz8 min
Module 1 Quiz12 min

2

Section
Clock
6 heures pour terminer

Module 2: Basic Natural Language Processing

...
Reading
3 vidéos (Total 36 min), 3 quiz
Video3 vidéos
Basic NLP tasks with NLTK16 min
Advanced NLP tasks with NLTK16 min
Quiz2 exercices pour s'entraîner
Practice Quiz4 min
Module 2 Quiz10 min

3

Section
Clock
7 heures pour terminer

Module 3: Classification of Text

...
Reading
7 vidéos (Total 94 min), 2 quiz
Video7 vidéos
Identifying Features from Text8 min
Naive Bayes Classifiers19 min
Naive Bayes Variations4 min
Support Vector Machines24 min
Learning Text Classifiers in Python15 min
Demonstration: Case Study - Sentiment Analysis9 min
Quiz1 exercice pour s'entraîner
Module 3 Quiz14 min

4

Section
Clock
6 heures pour terminer

Module 4: Topic Modeling

...
Reading
4 vidéos (Total 58 min), 2 lectures, 3 quiz
Video4 vidéos
Topic Modeling8 min
Generative Models and LDA13 min
Information Extraction18 min
Reading2 lectures
Additional Resources & Readings10 min
Post-Course Survey10 min
Quiz2 exercices pour s'entraîner
Practice Quiz4 min
Module 4 Quiz10 min
4.1
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a commencé une nouvelle carrière après avoir terminé ces cours
Briefcase

83%

a bénéficié d'un avantage concret dans sa carrière grâce à ce cours
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a obtenu une augmentation de salaire ou une promotion

Meilleurs avis

par 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!

par 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.

Enseignant

V. G. Vinod Vydiswaran

Assistant Professor
School of Information

À propos de 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....

À propos de la Spécialisation 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

Foire Aux Questions

  • 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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