【明尼苏达大学】推荐系统导论 #Introduction to Recommender Systems(英文)

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转载于www.coursera.com 如有侵权 联系删除! This course introduces the concepts, applications, algorithms, programming, and design of recommender systems--software systems that recommend products or information,
莫道桑榆晚,为霞尚满天
视频选集
(28/68)
01_introduction-to-recommender-systems
38:23
01_welcome-to-the-course
11:54
01_taxonomy-of-recommender-systems
27:58
01_taxonomy-of-recommender-systems-continued
23:22
01_amazon-tour
33:44
01_assignment-0-introduction
04:04
01_introduction-to-non-personalized-recommenders
32:53
01_preferences-and-ratings
17:22
01_predictions-and-recommendation
16:47
01_scales-and-normalization
22:26
01_interview-with-anthony-jameson-preferences-and-ratings
15:00
01_association-rules
07:37
01_assignment-1-introduction
01:51
01_introduction-to-content-based-recommenders
31:01
01_tfidf-and-more
24:10
01_content-based-recommenders-in-detail
29:27
01_tools-for-content-based-filtering
08:54
01_interview-with-robin-burke-entree-style-recommenders
13:38
02_interview-with-barry-smyth-case-based-reasoning
13:39
01_assignment-2-introduction
15:38
01_introduction-to-user-user-collaborative-filtering
20:26
01_basic-user-user-breakdown
24:17
01_variations-and-enhancements
33:37
01_explaining-recommendations
16:23
01_interview-with-paul-resnick-trust-reputation-influence-limiting
21:38
01_interview-with-jen-golbeck-trust-based-recommendation
15:57
01_interview-with-dan-cosley-impact-of-bad-ratings
13:06
01_assignment-3-introduction
12:50
01_intro-to-evaluation
16:48
01_basic-accuracy-metrics
20:58
01_basic-decision-support-metrics
27:47
01_rank-metrics
24:31
01_fallacy-of-hidden-data-evaluation
15:35
01_more-metrics
23:40
01_experimental-protocols
15:22
01_unary-data-evaluation
14:30
02_user-centered-evaluation
18:19
01_interview-with-neal-lathia-temporal-evaluation
12:50
02_interview-with-nava-tintarev-explanations
17:16
01_assignment-4-introduction
03:28
01_introduction-to-item-item-collaborative-filtering
20:13
01_item-item-algorithm
10:58
02_item-item-on-unary-data
10:04
03_item-item-hybrids-and-extensions
17:07
01_interview-with-brad-miller-practical-issues
16:05
02_interview-with-robin-burke-introduction-to-hybrid-algorithms
16:02
01_strengths-and-weaknesses-of-item-item-vs-user-user-cf
06:13
01_rise-and-fall-of-netperceptions
07:02
01_item-item-and-association-rules
04:08
01_normalization
05:18
01_assignment-5-introduction
05:21
01_introduction-to-dimensionality-reduction-recommenders
14:13
01_diving-deeper-with-svd
19:21
02_training-svds
16:44
01_funksvd-training-algorithm
09:04
01_probabilistic-matrix-factorization
17:28
02_extending-matrix-factorization
15:13
01_assignment-6-introduction
02:25
01_threat-models
12:17
02_the-cold-start-problem
13:27
01_what-wasn-t-covered
19:39
02_more-tools-for-recommendation
03:36
01_interview-with-anthony-jameson-groups
14:21
02_interview-with-francesco-ricci-context-aware-recommenders
20:55
01_interview-with-xavier-amatriain-learning-to-rank
20:48
01_interview-with-anmol-bhasin-industry-practial-issues
26:40
01_interview-with-pearl-pu-dialogue-based-recommenders
21:21
01_wrap-up
06:36
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