Acerca de este Curso

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Resultados profesionales del estudiante

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Certificado para compartir
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100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
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Aprox. 13 horas para completar
Inglés (English)
Subtítulos: Inglés (English)

Resultados profesionales del estudiante

50%

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.
Aprox. 13 horas para completar
Inglés (English)
Subtítulos: Inglés (English)

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Universidad de Minnesota

Programa - Qué aprenderás en este curso

Semana
1

Semana 1

4 minutos para completar

Preface

4 minutos para completar
1 video (Total 4 minutos)
Semana
2

Semana 2

1 hora para completar

Matrix Factorization (Part 1)

1 hora para completar
5 videos (Total 70 minutos), 1 lectura
5 videos
Singular Value Decomposition17m
Gradient Descent Techniques17m
Deriving FunkSVD11m
Probabilistic Matrix Factorization10m
1 lectura
On Folding-In with Gradient Descent10m
Semana
3

Semana 3

4 horas para completar

Matrix Factorization (Part 2)

4 horas para completar
2 videos (Total 15 minutos), 2 lecturas, 6 cuestionarios
2 videos
Programming Matrix Factorization6m
2 lecturas
Assignment Instructions10m
Intro - Programming Matrix Factorization10m
5 ejercicios de práctica
Matrix Factorization Assignment Part l10m
Matrix Factorization Assignment Part ll10m
Matrix Factorization Assignment Part lll10m
Matrix Factorization Quiz8m
SVD Programming Eval Quiz6m
Semana
4

Semana 4

2 horas para completar

Hybrid Recommenders

2 horas para completar
6 videos (Total 96 minutos)
6 videos
Hybrids with Robin Burke16m
Hybridization through Matrix Factorization15m
Matrix Factorization Hybrids with George Karypis17m
Interview with Arindam Banerjee15m
Interview with Yehuda Koren22m

Revisiones

Principales revisiones sobre MATRIX FACTORIZATION AND ADVANCED TECHNIQUES

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Acerca de Programa especializado: Sistemas de recomendación

A Recommender System is a process that seeks to predict user preferences. This Specialization covers all the fundamental techniques in recommender systems, from non-personalized and project-association recommenders through content-based and collaborative filtering techniques, as well as advanced topics like matrix factorization, hybrid machine learning methods for recommender systems, and dimension reduction techniques for the user-product preference space. This Specialization is designed to serve both the data mining expert who would want to implement techniques like collaborative filtering in their job, as well as the data literate marketing professional, who would want to gain more familiarity with these topics. The courses offer interactive, spreadsheet-based exercises to master different algorithms, along with an honors track where you can go into greater depth using the LensKit open source toolkit. By the end of this Specialization, you’ll be able to implement as well as evaluate recommender systems. The Capstone Project brings together the course material with a realistic recommender design and analysis project....
Sistemas de recomendación

Preguntas Frecuentes

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    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

  • 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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  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

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