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[Coursera] Recommender Systems (University of Minnesota) (recsys)

by: University of Minnesota

Publisher: Academic Torrents

Contributor: Academic Torrents

Academictorrents_collection: video-lectures

Addeddate: 2018-08-12 13:29:37

External-identifier: urn:academictorrents:42c3b47bf15a2a1aaadf92156f19315ad2d22967

Identifier: academictorrents_42c3b47bf15a2a1aaadf92156f19315ad2d22967

Ocr: ABBYY FineReader 11.0 (Extended OCR)

Ppi: 300

Scanner: Internet Archive Python library 1.8.1

Source: http://academictorrents.com/details/42c3b47bf15a2a1aaadf92156f19315ad2d22967
torrent:urn:sha1:42c3b47bf15a2a1aaadf92156f19315ad2d22967

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39 files

ABBYY GZ

BACK

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01_Video_4.1_-_Introduction_to_User-User_Collaborative_Filtering_20-25_jp2.zip

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02_Video_4.2_-_Basic_User-User_Breakdown_24-15_jp2.zip

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03_Video_4.3_-_Variations_and_Enhancements_33-36_jp2.zip

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04_Video_4.4_-_Explaining_Recommendations_16-22_jp2.zip

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01_Video_5.1_-_Intro_to_Evaluation_16-47_jp2.zip

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02_Video_5.2_-_Basic_Accuracy_Metrics_20-57_jp2.zip

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03_Video_5.3_-_Basic_Decision_Support_Metrics_27-46_jp2.zip

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04_Video_5.4_-_Rank_Metrics_24-18_jp2.zip

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05_Video_5.5_-_Fallacy_of_Hidden_Data_Evaluation_15-34_jp2.zip

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06_Video_5.6_-_More_Metrics_23-39_jp2.zip

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07_Video_5.7_-_Experimental_Protocols_15-21_jp2.zip

1.5M

08_Video_5.8_-_Unary_Data_Evaluation_14-29_jp2.zip

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09_Video_5.9_-_Using_the_LensKit_Evaluator_20-39_jp2.zip

2.0M

10_Video_5.10_-_User-Centered_Evaluation_18-18_jp2.zip

2.2M

01_Video_6.1_-_Introduction_to_Item-Item_Collaborative_Filtering_20-12_jp2.zip

1.6M

02_Video_6.2_-_Item-Item_Algorithm_10-57_jp2.zip

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03_Video_6.3_-_Item-Item_On_Unary_Data_10-03_jp2.zip

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04_Video_6.4_-_Item-Item_Hybrids_and_Extensions_17-06_jp2.zip

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03_Video_7.3_-_Training_SVDs_16-42_jp2.zip

1.7M

01_Video_8.1_-_Threat_Models_12-16_jp2.zip

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02_Video_8.2_-_The_Cold_Start_Problem_13-26_jp2.zip

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03_Video_8.3_-_What_wasnt_covered_19-36_jp2.zip

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04_Video_8.4_-_More_Tools_for_Recommendation_3-35_jp2.zip

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08_Video_8.5_-_Wrap_Up_18-28_jp2.zip

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02_Video_1.2_-_Welcome_to_the_Course_24-15.srt

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03_Video_1.3a_-_Software_Environment_6-47.srt

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04_Video_1.3b_-_Setup_of_Eclipse.srt

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05_Video_1.4a_-_Taxonomy_of_Recommender_Systems_27-57.srt

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06_Video_1.4b_-_Taxonomy_of_Recommender_Systems_continued_23-21.srt

41.4K

07_Video_1.5_-_Amazon_Tour_36-04.srt

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01_Video_2.1_-_Introduction_to_non-personalized_recommenders_32-52.srt

24.4K

02_Video_2.2_-_Preferences_and_Ratings_17-21.srt

19.8K

03_Video_2.3_-_Predictions_and_Recommendations_16-46.srt

29.5K

04_Video_2.4_-_Scales_and_Normalization_20-35.srt

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05_Interview_with_Anthony_Jameson_-_Preferences_and_Ratings_14-59.srt

39.4K

01_Video_3.1_-_Introduction_to_Content-Based_Recommenders_30-59.srt

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02_Video_3.2_-_Introduction_to_LensKit_36-13.srt

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03_Video_3.3_-_TFIDF_and_more_24-09.srt

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05_Video_3.5_-_Tools_for_Content-Based_Filtering_8-53.srt

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06_Case-Based_Reasoning_-_Interview_with_Barry_Smyth_-_13-09.srt

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07_LensKit_Example_Walkthrough_27-14.srt

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01_Video_4.1_-_Introduction_to_User-User_Collaborative_Filtering_20-25.srt

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02_Video_4.2_-_Basic_User-User_Breakdown_24-15.srt

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03_Video_4.3_-_Variations_and_Enhancements_33-36.srt

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04_Video_4.4_-_Explaining_Recommendations_16-22.srt

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05_Trust_Reputation_Influence_Limiting_-_Interview_with_Paul_Resnick_21-37.srt

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06_Trust-Based_Recommendation_-_Interview_with_Jen_Golbeck_15-56.srt

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01_Video_5.1_-_Intro_to_Evaluation_16-47.srt

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03_Video_5.3_-_Basic_Decision_Support_Metrics_27-46.srt

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04_Video_5.4_-_Rank_Metrics_24-18.srt

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05_Video_5.5_-_Fallacy_of_Hidden_Data_Evaluation_15-34.srt

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07_Video_5.7_-_Experimental_Protocols_15-21.srt

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08_Video_5.8_-_Unary_Data_Evaluation_14-29.srt

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10_Video_5.10_-_User-Centered_Evaluation_18-18.srt

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01_Video_6.1_-_Introduction_to_Item-Item_Collaborative_Filtering_20-12.srt

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02_Video_6.2_-_Item-Item_Algorithm_10-57.srt

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03_Video_6.3_-_Item-Item_On_Unary_Data_10-03.srt

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01_Video_7.1_-_Introduction_to_Dimensionality_Reduction_Recommenders_14-13.srt

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02_Video_7.2_-_Diving_Deeper_with_SVD_19-18.srt

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03_Video_7.3_-_Training_SVDs_16-42.srt

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04_Video_7.4_-_FunkSVD_Training_Algorithm_9-03.srt

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05_Video_7.5_-_Probabilistic_Matrix_Factorization_17-28.srt

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01_Video_8.1_-_Threat_Models_12-16.srt

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02_Video_8.2_-_The_Cold_Start_Problem_13-26.srt

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03_Video_8.3_-_What_wasnt_covered_19-36.srt

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04_Video_8.4_-_More_Tools_for_Recommendation_3-35.srt

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05_Groups_-_Interview_with_Anthony_Jameson_14-20.srt

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06_Context-Aware_Recommenders_-_Interview_with_Francesco_Ricci_20-54.srt

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07_Learning_to_Rank_-_Interview_with_Xavier_Amatriain_20-47.srt

51 files

TEXT

BACK

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01_Video_1.1_-_Introduction_to_Recommender_Systems_38-22.txt

20.4K

02_Video_1.2_-_Welcome_to_the_Course_24-15.txt

4.8K

03_Video_1.3a_-_Software_Environment_6-47.txt

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04_Video_1.3b_-_Setup_of_Eclipse.txt

20.0K

05_Video_1.4a_-_Taxonomy_of_Recommender_Systems_27-57.txt

15.7K

06_Video_1.4b_-_Taxonomy_of_Recommender_Systems_continued_23-21.txt

24.6K

07_Video_1.5_-_Amazon_Tour_36-04.txt

24.2K

01_Video_2.1_-_Introduction_to_non-personalized_recommenders_32-52.txt

14.7K

02_Video_2.2_-_Preferences_and_Ratings_17-21.txt

12.1K

03_Video_2.3_-_Predictions_and_Recommendations_16-46.txt

17.8K

04_Video_2.4_-_Scales_and_Normalization_20-35.txt

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05_Interview_with_Anthony_Jameson_-_Preferences_and_Ratings_14-59.txt

23.7K

01_Video_3.1_-_Introduction_to_Content-Based_Recommenders_30-59.txt

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02_Video_3.2_-_Introduction_to_LensKit_36-13.txt

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03_Video_3.3_-_TFIDF_and_more_24-09.txt

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04_Video_3.4_-_Content-Based_Recommenders_in_Detail_29-26.txt

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05_Video_3.5_-_Tools_for_Content-Based_Filtering_8-53.txt

12.0K

06_Case-Based_Reasoning_-_Interview_with_Barry_Smyth_-_13-09.txt

19.9K

07_LensKit_Example_Walkthrough_27-14.txt

15.8K

01_Video_4.1_-_Introduction_to_User-User_Collaborative_Filtering_20-25.txt

15.2K

02_Video_4.2_-_Basic_User-User_Breakdown_24-15.txt

22.0K

03_Video_4.3_-_Variations_and_Enhancements_33-36.txt

12.7K

04_Video_4.4_-_Explaining_Recommendations_16-22.txt

17.3K

05_Trust_Reputation_Influence_Limiting_-_Interview_with_Paul_Resnick_21-37.txt

15.7K

06_Trust-Based_Recommendation_-_Interview_with_Jen_Golbeck_15-56.txt

13.0K

01_Video_5.1_-_Intro_to_Evaluation_16-47.txt

15.2K

02_Video_5.2_-_Basic_Accuracy_Metrics_20-57.txt

21.0K

03_Video_5.3_-_Basic_Decision_Support_Metrics_27-46.txt

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04_Video_5.4_-_Rank_Metrics_24-18.txt

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05_Video_5.5_-_Fallacy_of_Hidden_Data_Evaluation_15-34.txt

18.0K

06_Video_5.6_-_More_Metrics_23-39.txt

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07_Video_5.7_-_Experimental_Protocols_15-21.txt

12.5K

08_Video_5.8_-_Unary_Data_Evaluation_14-29.txt

15.2K

09_Video_5.9_-_Using_the_LensKit_Evaluator_20-39.txt

15.2K

10_Video_5.10_-_User-Centered_Evaluation_18-18.txt

14.8K

01_Video_6.1_-_Introduction_to_Item-Item_Collaborative_Filtering_20-12.txt

9.0K

02_Video_6.2_-_Item-Item_Algorithm_10-57.txt

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03_Video_6.3_-_Item-Item_On_Unary_Data_10-03.txt

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04_Video_6.4_-_Item-Item_Hybrids_and_Extensions_17-06.txt

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01_Video_7.1_-_Introduction_to_Dimensionality_Reduction_Recommenders_14-13.txt

13.7K

02_Video_7.2_-_Diving_Deeper_with_SVD_19-18.txt

11.6K

03_Video_7.3_-_Training_SVDs_16-42.txt

4.6K

04_Video_7.4_-_FunkSVD_Training_Algorithm_9-03.txt

12.7K

05_Video_7.5_-_Probabilistic_Matrix_Factorization_17-28.txt

11.1K

01_Video_8.1_-_Threat_Models_12-16.txt

11.2K

02_Video_8.2_-_The_Cold_Start_Problem_13-26.txt

16.3K

03_Video_8.3_-_What_wasnt_covered_19-36.txt

3.2K

04_Video_8.4_-_More_Tools_for_Recommendation_3-35.txt

13.9K

05_Groups_-_Interview_with_Anthony_Jameson_14-20.txt

18.5K

06_Context-Aware_Recommenders_-_Interview_with_Francesco_Ricci_20-54.txt

17.6K

07_Learning_to_Rank_-_Interview_with_Xavier_Amatriain_20-47.txt

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[Coursera] Recommender Systems (University of Minnesota) (recsys)

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