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BuildYourOwnRecommendationEngines

por BHU L. 1,142,475 KB • 56 archivos

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01 - The Course Overview - Learning Path Build Your Own Recommendation Engines.mp4
01 - The Course Overview - Learning Path Build Your Own Recommendation Engines.mp4
02 - Recommendation engine definition - Learning Path Build Your Own Recommendation Engines.mp4
02 - Recommendation engine definition - Learning Path Build Your Own Recommendation Engines.mp4
03 - Types of recommender systems.mp4
03 - Types of recommender systems.mp4
04 - Evolution of recommender systems with technology.mp4
04 - Evolution of recommender systems with technology.mp4
05 - Loading and formatting data.mp4
05 - Loading and formatting data.mp4
06 - Calculating similarity between users.mp4
06 - Calculating similarity between users.mp4
07 - Predicting the unknown ratings for users.mp4
07 - Predicting the unknown ratings for users.mp4
08 - Nearest neighborhood-based recommendation engines.mp4
08 - Nearest neighborhood-based recommendation engines.mp4
09 - Content-based recommender system.mp4
09 - Content-based recommender system.mp4
10 - Context-aware recommender system.mp4
10 - Context-aware recommender system.mp4
11 - Hybrid recommender systems.mp4
11 - Hybrid recommender systems.mp4
12 - Model-based recommender systems.mp4
12 - Model-based recommender systems.mp4
13 - Neighborhood-based techniques.mp4
13 - Neighborhood-based techniques.mp4
14 - Mathematical model techniques.mp4
14 - Mathematical model techniques.mp4
15 - Machine learning techniques.mp4
15 - Machine learning techniques.mp4
16 - Classification models.mp4
16 - Classification models.mp4
17 - Clustering techniques and dimensionality reduction.mp4
17 - Clustering techniques and dimensionality reduction.mp4
18 - Vector space models.mp4
18 - Vector space models.mp4
19 - Evaluation techniques.mp4
19 - Evaluation techniques.mp4
20 - Installing the recommenderlab package in RStudio.mp4
20 - Installing the recommenderlab package in RStudio.mp4
21 - Datasets available in the recommenderlab package.mp4
21 - Datasets available in the recommenderlab package.mp4
22 - Exploring the dataset andbuilding user-based collaborative filtering.mp4
22 - Exploring the dataset andbuilding user-based collaborative filtering.mp4
23 - Building an item-based recommender model.mp4
23 - Building an item-based recommender model.mp4
24 - Collaborative filtering using Python.mp4
24 - Collaborative filtering using Python.mp4
25 - Data exploration.mp4
25 - Data exploration.mp4
26 - User-based collaborative filtering with the k-nearest neighbors.mp4
26 - User-based collaborative filtering with the k-nearest neighbors.mp4
27 - Item-based recommendations.mp4
27 - Item-based recommendations.mp4
28 - The Course Overview.mp4
28 - The Course Overview.mp4
29 - Personalized and Content-Based Recommender System.mp4
29 - Personalized and Content-Based Recommender System.mp4
30 - Content-Based Recommendation Using Python.mp4
30 - Content-Based Recommendation Using Python.mp4

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