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).
Este curso forma parte de Programa Especializado - Ciencias de los Datos Aplicada con Python
ofrecido por
Programa Especializado - Ciencias de los Datos Aplicada con PythonUniversidad de MíchiganAcerca de este Curso
154,066 vistas recientes
Resultados profesionales del estudiante
29%
comenzó una nueva carrera después de completar estos cursos
32%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio
Aprox. 29 horas para completar
Inglés (English)
Subtítulos: Inglés (English), Coreano
Qué aprenderás
Understand how text is handled in Python
Apply basic natural language processing methods
Write code that groups documents by topic
Describe the nltk framework for manipulating text
Habilidades que obtendrás
Natural Language Toolkit (NLTK)Text MiningPython ProgrammingNatural Language Processing
Resultados profesionales del estudiante
29%
comenzó una nueva carrera después de completar estos cursos
32%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio
Aprox. 29 horas para completar
Inglés (English)
Subtítulos: Inglés (English), Coreano
ofrecido por
Universidad de Míchigan
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.
Programa - Qué aprenderás en este curso
9 horas para completar
Module 1: Working with Text in Python
9 horas para completar
5 videos (Total 56 minutos), 4 lecturas, 3 cuestionarios
5 videos
Handling Text in Python18m
Regular Expressions16m
Demonstration: Regex with Pandas and Named Groups5m
Internationalization and Issues with Non-ASCII Characters12m
4 lecturas
Course Syllabus10m
Help us learn more about you!!10m
Notice for Auditing Learners: Assignment Submission10m
Resources: Common issues with free text10m
2 ejercicios de práctica
Practice Quiz30m
Module 1 Quiz30m
7 horas para completar
Module 2: Basic Natural Language Processing
7 horas para completar
3 videos (Total 36 minutos)
3 videos
Basic NLP tasks with NLTK16m
Advanced NLP tasks with NLTK16m
2 ejercicios de práctica
Practice Quiz30m
Module 2 Quiz30m
7 horas para completar
Module 3: Classification of Text
7 horas para completar
7 videos (Total 94 minutos)
7 videos
Identifying Features from Text8m
Naive Bayes Classifiers19m
Naive Bayes Variations4m
Support Vector Machines24m
Learning Text Classifiers in Python15m
Demonstration: Case Study - Sentiment Analysis9m
1 ejercicio de práctica
Module 3 Quiz30m
6 horas para completar
Module 4: Topic Modeling
6 horas para completar
4 videos (Total 58 minutos), 3 lecturas, 3 cuestionarios
4 videos
Topic Modeling8m
Generative Models and LDA13m
Information Extraction18m
3 lecturas
Additional Resources & Readings10m
Post-Course Survey10m
Keep Learning with Michigan Online10m
2 ejercicios de práctica
Practice Quiz30m
Module 4 Quiz30m
Reseñas
Principales reseñas sobre APPLIED TEXT MINING IN PYTHON
por RK19 de jul. de 2019
Course is great except for the auto grader issues. Please look into the issue. I would like to take this opportunity and thank Prof V. G. Vinod Vydiswaran and all those who helped me to complete it.
por CC26 de ago. de 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 LC16 de feb. de 2018
Love the focus on conceptual text processing and practical guides to implementation in python, but the assignment grader was extremely specific for no reason, especially the Week3 assignment.
por GK3 de may. de 2019
Lectures are very good with a perfect explanation. More than lectures I liked the assignment questions. They are worth doing. You will get to know the basic foundation of text mining. :-)
Acerca de Programa especializado: Ciencias de los Datos Aplicada con 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.
Preguntas Frecuentes
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