Acerca de este Curso
4.4
325 calificaciones
89 revisiones
Programa Especializado
100 % en línea

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Horas para completar

Aprox. 20 horas para completar

Sugerido: 6 hours/week...
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English)

Habilidades que obtendrás

Data Clustering AlgorithmsText MiningProbabilistic ModelsSentiment Analysis
Programa Especializado
100 % en línea

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Horas para completar

Aprox. 20 horas para completar

Sugerido: 6 hours/week...
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English)

Programa - Qué aprenderás en este curso

Semana
1
Horas para completar
2 horas para completar

Orientation

You will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course....
Reading
2 videos (Total 15 minutos), 5 readings, 2 quizzes
Video2 videos
Course Prerequisites & Completion6m
Reading5 lecturas
Welcome to Text Mining and Analytics!10m
Syllabus15m
About the Discussion Forums15m
Updating your Profile10m
Social Media10m
Quiz2 ejercicios de práctica
Orientation Quiz15m
Pre-Quiz26m
Horas para completar
4 horas para completar

Week 1

During this module, you will learn the overall course design, an overview of natural language processing techniques and text representation, which are the foundation for all kinds of text-mining applications, and word association mining with a particular focus on mining one of the two basic forms of word associations (i.e., paradigmatic relations). ...
Reading
9 videos (Total 109 minutos), 1 reading, 2 quizzes
Video9 videos
1.2 Overview Text Mining and Analytics: Part 211m
1.3 Natural Language Content Analysis: Part 112m
1.4 Natural Language Content Analysis: Part 24m
1.5 Text Representation: Part 110m
1.6 Text Representation: Part 29m
1.7 Word Association Mining and Analysis15m
1.8 Paradigmatic Relation Discovery Part 114m
1.9 Paradigmatic Relation Discovery Part 217m
Reading1 lectura
Week 1 Overview10m
Quiz2 ejercicios de práctica
Week 1 Practice Quizs
Week 1 Quizs
Semana
2
Horas para completar
4 horas para completar

Week 2

During this module, you will learn more about word association mining with a particular focus on mining the other basic form of word association (i.e., syntagmatic relations), and start learning topic analysis with a focus on techniques for mining one topic from text. ...
Reading
10 videos (Total 116 minutos), 1 reading, 2 quizzes
Video10 videos
2.2 Syntagmatic Relation Discovery: Conditional Entropy11m
2.3 Syntagmatic Relation Discovery: Mutual Information: Part 113m
2.4 Syntagmatic Relation Discovery: Mutual Information: Part 29m
2.5 Topic Mining and Analysis: Motivation and Task Definition7m
2.6 Topic Mining and Analysis: Term as Topic11m
2.7 Topic Mining and Analysis: Probabilistic Topic Models14m
2.8 Probabilistic Topic Models: Overview of Statistical Language Models: Part 110m
2.9 Probabilistic Topic Models: Overview of Statistical Language Models: Part 213m
2.10 Probabilistic Topic Models: Mining One Topic12m
Reading1 lectura
Week 2 Overview10m
Quiz2 ejercicios de práctica
Week 2 Practice Quizs
Week 2 Quizs
Semana
3
Horas para completar
10 horas para completar

Week 3

During this module, you will learn topic analysis in depth, including mixture models and how they work, Expectation-Maximization (EM) algorithm and how it can be used to estimate parameters of a mixture model, the basic topic model, Probabilistic Latent Semantic Analysis (PLSA), and how Latent Dirichlet Allocation (LDA) extends PLSA. ...
Reading
10 videos (Total 103 minutos), 2 readings, 3 quizzes
Video10 videos
3.2 Probabilistic Topic Models: Mixture Model Estimation: Part 110m
3.3 Probabilistic Topic Models: Mixture Model Estimation: Part 28m
3.4 Probabilistic Topic Models: Expectation-Maximization Algorithm: Part 111m
3.5 Probabilistic Topic Models: Expectation-Maximization Algorithm: Part 210m
3.6 Probabilistic Topic Models: Expectation-Maximization Algorithm: Part 36m
3.7 Probabilistic Latent Semantic Analysis (PLSA): Part 110m
3.8 Probabilistic Latent Semantic Analysis (PLSA): Part 210m
3.9 Latent Dirichlet Allocation (LDA): Part 110m
3.10 Latent Dirichlet Allocation (LDA): Part 212m
Reading2 lecturas
Week 3 Overview10m
Programming Assignments Overview10m
Quiz2 ejercicios de práctica
Week 3 Practice Quizs
Quiz: Week 3 Quizs
Semana
4
Horas para completar
5 horas para completar

Week 4

During this module, you will learn text clustering, including the basic concepts, main clustering techniques, including probabilistic approaches and similarity-based approaches, and how to evaluate text clustering. You will also start learning text categorization, which is related to text clustering, but with pre-defined categories that can be viewed as pre-defining clusters. ...
Reading
9 videos (Total 141 minutos), 1 reading, 2 quizzes
Video9 videos
4.2 Text Clustering: Generative Probabilistic Models Part 116m
4.3 Text Clustering: Generative Probabilistic Models Part 28m
4.4 Text Clustering: Generative Probabilistic Models Part 314m
4.5 Text Clustering: Similarity-based Approaches17m
4.6 Text Clustering: Evaluation10m
4.7 Text Categorization: Motivation14m
4.8 Text Categorization: Methods11m
4.9 Text Categorization: Generative Probabilistic Models31m
Reading1 lectura
Week 4 Overview10m
Quiz2 ejercicios de práctica
Week 4 Practice Quizs
Week 4 Quizs
4.4
89 revisionesChevron Right
Dirección de la carrera

33%

comenzó una nueva carrera después de completar estos cursos
Beneficio de la carrera

57%

consiguió un beneficio tangible en su carrera profesional gracias a este curso
Promoción de la carrera

17%

consiguió un aumento de sueldo o ascenso

Principales revisiones

por JHFeb 10th 2017

Excellent course, the pipeline they propose to help you understand text mining is quite helpful. It has an important introduction to the most key concepts and techniques for text mining and analytics.

por DCMar 25th 2018

The content of Text Mining and Analytics is very comprehensive and deep. More practise about how formula works would be better. Quiz could be not tough to be completed after attending every lectures.

Instructor

Avatar

ChengXiang Zhai

Professor
Department of Computer Science
Graduation Cap

Comienza a trabajar para obtener tu maestría

Este curso es parte del Master in Computer Science completamente en línea de University of Illinois at Urbana-Champaign. Si eres aceptado en el programa completo, tus cursos cuentan para tu título.

Acerca de University of Illinois at Urbana-Champaign

The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs. ...

Acerca del programa especializado Data Mining

The Data Mining Specialization teaches data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of natural language text. Specific course topics include pattern discovery, clustering, text retrieval, text mining and analytics, and data visualization. The Capstone project task is to solve real-world data mining challenges using a restaurant review data set from Yelp. Courses 2 - 5 of this Specialization form the lecture component of courses in the online Master of Computer Science Degree in Data Science. You can apply to the degree program either before or after you begin the Specialization....
Data Mining

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.

¿Tienes más preguntas? Visita el Centro de Ayuda al Alumno.