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
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Programa especializado: Ciencias de los Datos Aplicada con PythonUniversidad de MíchiganAcerca de este Curso
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Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
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Nivel intermedio
Aprox. 29 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Italiano, Vietnamita, Coreano, Alemán (German), Ruso (Russian), Inglés (English), Español (Spanish)
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 Mining
- Python Programming
- Natural Language Processing
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Nivel intermedio
Aprox. 29 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Italiano, Vietnamita, Coreano, Alemán (German), Ruso (Russian), Inglés (English), Español (Spanish)
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
7 horas para completar
Module 2: Basic Natural Language Processing
7 horas para completar
3 videos (Total 36 minutos)
7 horas para completar
Module 3: Classification of Text
7 horas para completar
7 videos (Total 94 minutos)
6 horas para completar
Module 4: Topic Modeling
6 horas para completar
4 videos (Total 58 minutos), 3 lecturas, 3 cuestionarios
Reseñas
- 5 stars55,14 %
- 4 stars25,27 %
- 3 stars11,96 %
- 2 stars4,29 %
- 1 star3,31 %
Principales reseñas sobre APPLIED TEXT MINING IN PYTHON
por TK22 de jun. de 2020
Everything was awesome, assignment 2 was my favorite in a long while in this specialization series. Week 4 was a little weak, and felt rushed. Overall, I enjoyed this course 4 of the 5.
por JR4 de dic. de 2020
Excellent course to get started with text mining and NLP with Python. The course goes over the most essential elements involved with dealing with free text. Definitely worth the time I spent on it.
por CB19 de sep. de 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
por VL27 de dic. de 2020
It is a great course with challenging assignments, I wish the syllabus is a little more deeper specially on the LDA part. But overall a good course that one can look for!
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.
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