Acerca de este Curso
4.2
1,171 calificaciones
•
227 revisiones
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....
Stacks

Curso 4 de 5 en

Programa especializado Applied Data Science with Python
Globe

Cursos 100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Calendar

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Intermediate Level

Nivel intermedio

Clock

Approx. 17 hours to complete

Sugerido: 8 hours/week...
Comment Dots

English

Subtítulos: English...

Qué aprenderás

  • 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

Habilidades que obtendrás

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

Curso 4 de 5 en

Programa especializado Applied Data Science with Python
Globe

Cursos 100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Calendar

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Intermediate Level

Nivel intermedio

Clock

Approx. 17 hours to complete

Sugerido: 8 hours/week...
Comment Dots

English

Subtítulos: English...

Programa - Qué aprenderás en este curso

Week
1
Clock
8 horas para completar

Module 1: Working with Text in Python

...
Reading
5 videos (Total: 56 min), 4 readings, 3 quizzes
Video5 videos
Introduction to Text Mining3m
Handling Text in Python18m
Regular Expressions16m
Demonstration: Regex with Pandas and Named Groups5m
Internationalization and Issues with Non-ASCII Characters12m
Reading4 lecturas
Course Syllabus10m
Help us learn more about you!10m
Notice for Auditing Learners: Assignment Submission10m
Resources: Common issues with free text10m
Quiz2 ejercicios de práctica
Practice Quiz8m
Module 1 Quiz12m
Week
2
Clock
6 horas para completar

Module 2: Basic Natural Language Processing

...
Reading
3 videos (Total: 36 min), 3 quizzes
Video3 videos
Basic Natural Language Processing3m
Basic NLP tasks with NLTK16m
Advanced NLP tasks with NLTK16m
Quiz2 ejercicios de práctica
Practice Quiz4m
Module 2 Quiz10m
Week
3
Clock
7 horas para completar

Module 3: Classification of Text

...
Reading
7 videos (Total: 94 min), 2 quizzes
Video7 videos
Text Classification12m
Identifying Features from Text8m
Naive Bayes Classifiers19m
Naive Bayes Variations4m
Support Vector Machines24m
Learning Text Classifiers in Python15m
Demonstration: Case Study - Sentiment Analysis9m
Quiz1 ejercicio de práctica
Module 3 Quiz14m
Week
4
Clock
6 horas para completar

Module 4: Topic Modeling

...
Reading
4 videos (Total: 58 min), 2 readings, 3 quizzes
Video4 videos
Semantic Text Similarity17m
Topic Modeling8m
Generative Models and LDA13m
Information Extraction18m
Reading2 lecturas
Additional Resources & Readings10m
Post-Course Survey10m
Quiz2 ejercicios de práctica
Practice Quiz4m
Module 4 Quiz10m
4.2
Direction Signs

20%

comenzó una nueva carrera después de completar estos cursos
Briefcase

83%

consiguió un beneficio tangible en su carrera profesional gracias a este curso
Money

10%

consiguió un aumento de sueldo o ascenso

Principales revisiones

por CC•Aug 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!

por CB•Sep 20th 2017

Excellent course! Video lectures are high quality, with realistic problems and applications. Exercises are reasonably challenging, and all quite fun to do! Strongly recommend this course

Instructor

V. G. Vinod Vydiswaran

Assistant Professor
School of Information

Acerca 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....

Acerca del programa especializado 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 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

Preguntas Frecuentes

  • Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.

  • Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.

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