Internet Archive's in-browser video player requires JavaScript to be enabled. It appears your browser does not have it turned on. Please see your browser settings for this feature.

[Coursera] Mining Massive Datasets (Stanford University) (mmds)

by: Stanford University

Publisher: Academic Torrents

Contributor: Academic Torrents

Academictorrents_collection: video-lectures

Addeddate: 2018-08-12 13:36:04

External-identifier: urn:academictorrents:91bc48e6c8341de198c970acccdc87199391ab46

Identifier: academictorrents_91bc48e6c8341de198c970acccdc87199391ab46

Ocr: ABBYY FineReader 11.0 (Extended OCR)

Ppi: 600

Scanner: Internet Archive Python library 1.8.1

Source: http://academictorrents.com/details/91bc48e6c8341de198c970acccdc87199391ab46
torrent:urn:sha1:91bc48e6c8341de198c970acccdc87199391ab46

plus-circle Add Review

comment
Reviews

There are no reviews yet. Be the first one to write a review.

6,765 Views

3 Favorites

DOWNLOAD OPTIONS

94 files

ABBYY GZ

BACK

51.2K

01_Distributed_File_Systems_15-50_abbyy.gz

62.7K

02_The_MapReduce_Computational_Model_22-04_abbyy.gz

36.9K

03_Scheduling_and_Data_Flow_12-43_abbyy.gz

56.2K

04_Combiners_and_Partition_Functions_12-17_Advanced_abbyy.gz

101.0K

05_Link_Analysis_and_PageRank_9-39_abbyy.gz

37.7K

06_PageRank-_The_Flow_Formulation_9-16_abbyy.gz

33.9K

07_PageRank-_The_Matrix_Formulation_8-02_abbyy.gz

52.1K

08_PageRank-_Power_Iteration_10-34_abbyy.gz

55.5K

09_PageRank-_The_Google_Formulation_12-08_abbyy.gz

51.8K

10_Why_Teleports_Solve_the_Problem_12-26_abbyy.gz

59.8K

11_How_we_Really_Compute_PageRank_13-49_abbyy.gz

43.0K

01_Finding_Similar_Sets_13-37_abbyy.gz

73.7K

02_Minhashing_25-18_abbyy.gz

54.1K

03_Locality-Sensitive_Hashing_19-24_abbyy.gz

44.7K

04_Applications_of_LSH_11-40_abbyy.gz

36.8K

05_Fingerprint_Matching_7-07_abbyy.gz

33.9K

06_Finding_Duplicate_News_Articles_6-08_abbyy.gz

91.5K

07_Distance_Measures_22-39_abbyy.gz

59.0K

08_Nearest_Neighbor_Learning_11-39_abbyy.gz

101.2K

09_Frequent_Itemsets_29-50_abbyy.gz

40.4K

10_A-Priori_Algorithm_13-07_abbyy.gz

69.8K

11_Improvements_to_A-Priori_17-26__Advanced_abbyy.gz

73.0K

12_All_or_Most_Frequent_Itemsets_in_2_Passes_14-40_Advanced_abbyy.gz

54.0K

01_Community_Detection_in_Graphs-_Motivation_5-44_abbyy.gz

33.9K

02_The_Affiliation_Graph_Model_10-04_abbyy.gz

34.5K

03_From_AGM_to_BIGCLAM_8-48_abbyy.gz

46.3K

04_Solving_the_BIGCLAM_9-19_abbyy.gz

45.2K

05_Detecting_Communities_as_Clusters_8-39_Advanced_abbyy.gz

36.4K

06_What_Makes_a_Good_Cluster_8-48_Advanced_abbyy.gz

33.4K

07_The_Graph_Laplacian_Matrix_6-51_Advanced_abbyy.gz

18.8K

08_Examples_of_Eigendecompositions_of_Graphs_6-16_Advanced_abbyy.gz

21.3K

09_Defining_the_Graph_Laplacian_3-27_Advanced_abbyy.gz

42.3K

10_Spectral_Graph_Partitioning-_Finding_a_Partition_13-25_Advanced_abbyy.gz

51.6K

11_Spectral_Clustering-_Three_Steps_7-17_Advanced_abbyy.gz

72.6K

12_Analysis_of_Large_Graphs-_Trawling_9-02_Advanced_abbyy.gz

43.2K

13_Mining_Data_Streams_12-01_abbyy.gz

84.7K

14_Counting_1s_29-00_Advanced_abbyy.gz

67.6K

15_Bloom_Filters_18-00_abbyy.gz

51.7K

16_Sampling_a_Stream_11-30_abbyy.gz

79.2K

17_Counting_Distinct_Elements_25-59_Advanced_abbyy.gz

49.2K

01_Overview_of_Recommender_Systems_16-51_abbyy.gz

59.3K

02_Content-Based_Recommendations_21-00_abbyy.gz

82.7K

03_Collaborative_Filtering_20-52_abbyy.gz

43.6K

04_Implementing_Collaborative_Filtering_13-46_Advanced_abbyy.gz

20.2K

05_Evaluating_Recommender_Systems_6-09_abbyy.gz

53.2K

06_Dimensionality_Reduction-_Introduction_12-01_abbyy.gz

89.4K

07_Singular-Value_Decomposition_13-39_abbyy.gz

86.0K

08_Dimensionality_Reduction_with_SVD_9-04_abbyy.gz

50.2K

09_SVD_Gives_the_Best_Low-Rank_Approximation_8-28_Advanced_abbyy.gz

77.7K

10_SVD_Example_and_Conclusion_11-58_abbyy.gz

55.0K

11_CUR_Decomposition_6-27_Advanced_abbyy.gz

28.2K

12_The_CUR_Algorithm_6-15_Advanced_abbyy.gz

33.6K

13_Discussion_of_the_CUR_Method_7-09_abbyy.gz

70.9K

14_Latent-Factor_Models_16-11_abbyy.gz

124.4K

15_Latent-Factor_Recommender_System_14-16_abbyy.gz

108.6K

16_Finding_the_Latent_Factors_13-20_abbyy.gz

97.5K

17_Extension_to_Include_Global_Effects_9-42_Advanced_abbyy.gz

49.4K

01_Overview_of_Clustering_8-46_abbyy.gz

59.6K

02_Hierarchical_Clustering_14-07_abbyy.gz

43.4K

03_The_k-Means_Algorithm_12-49_abbyy.gz

92.4K

04_The_BFR_Algorithm_25-01_abbyy.gz

32.0K

05_The_CURE_Algorithm_15-13_Advanced_abbyy.gz

59.2K

06_Computational_Advertising-_Bipartite_Graph_Matching_24-47_abbyy.gz

95.6K

07_The_AdWords_Problem_19-21_abbyy.gz

58.4K

08_The_Balance_Algorithm_15-16_abbyy.gz

36.9K

09_Generalized_Balance_14-35_Advanced_abbyy.gz

26.7K

01_Support_Vector_Machines-_Introduction_7-30_abbyy.gz

46.7K

02_Support_Vector_Machines-_Mathematical_Formulation_12-15_abbyy.gz

29.0K

03_What_is_the_Margin_8-22_abbyy.gz

31.2K

04_Soft-Margin_SVMs_9-46_abbyy.gz

77.0K

05_How_to_Compute_the_Margin_14-36_Advanced_abbyy.gz

45.5K

06_Support_Vector_Machines-_Example_7-07_abbyy.gz

30.9K

07_Decision_Trees_8-33_abbyy.gz

70.1K

08_How_to_Construct_a_Tree_13-21_abbyy.gz

66.7K

09_Information_Gain_9-50_abbyy.gz

80.6K

10_Building_Decision_Trees_Using_MapReduce_8-14_Advanced_abbyy.gz

39.0K

11_Decision_Trees-_Conclusion_7-25_abbyy.gz

44.5K

12_MapReduce_Algorithms_Part_I_10-51_Advanced_abbyy.gz

64.6K

13_MapReduce_Algorithms_Part_II_9-46_Advanced_abbyy.gz

91.7K

14_Theory_of_MapReduce_Algorithms_19-39_Advanced_abbyy.gz

103.5K

15_Matrix_Multiplication_in_MapReduce_24-48_Advanced_abbyy.gz

84.4K

01_LSH_Families_21-13_abbyy.gz

49.0K

02_More_About_LSH_Families_12-57_abbyy.gz

35.9K

03_Sets_and_Strings_With_a_High_Degree_of_Similarity_11-29_Advanced_abbyy.gz

24.3K

04_Prefix_of_a_String_7-43_Advanced_abbyy.gz

37.7K

05_Positions_Within_Prefixes_14-04_Advanced_abbyy.gz

45.7K

06_Exploiting_Length_14-39_Advanced_abbyy.gz

71.0K

07_Computing_PageRank_on_Big_Graphs_10-18_Advanced_abbyy.gz

52.2K

08_Topic-Specific_PageRank_10-06_abbyy.gz

37.6K

09_Application_to_Measuring_Proximity_in_Graphs_6-25_abbyy.gz

101.6K

10_Hubs_and_Authorities_15-16_Advanced_abbyy.gz

72.8K

11_Web_Spam-_Introduction_6-50_abbyy.gz

49.6K

12_Spam_Farms_8-00_abbyy.gz

59.5K

13_TrustRank_10-05_abbyy.gz

94 files

FULL TEXT

BACK

2.9K

01_Distributed_File_Systems_15-50_djvu.txt

3.6K

02_The_MapReduce_Computational_Model_22-04_djvu.txt

2.1K

03_Scheduling_and_Data_Flow_12-43_djvu.txt

3.2K

04_Combiners_and_Partition_Functions_12-17_Advanced_djvu.txt

5.3K

05_Link_Analysis_and_PageRank_9-39_djvu.txt

2.1K

06_PageRank-_The_Flow_Formulation_9-16_djvu.txt

1.7K

07_PageRank-_The_Matrix_Formulation_8-02_djvu.txt

2.9K

08_PageRank-_Power_Iteration_10-34_djvu.txt

3.0K

09_PageRank-_The_Google_Formulation_12-08_djvu.txt

2.8K

10_Why_Teleports_Solve_the_Problem_12-26_djvu.txt

3.0K

11_How_we_Really_Compute_PageRank_13-49_djvu.txt

2.6K

01_Finding_Similar_Sets_13-37_djvu.txt

4.2K

02_Minhashing_25-18_djvu.txt

3.2K

03_Locality-Sensitive_Hashing_19-24_djvu.txt

2.8K

04_Applications_of_LSH_11-40_djvu.txt

2.1K

05_Fingerprint_Matching_7-07_djvu.txt

2.1K

06_Finding_Duplicate_News_Articles_6-08_djvu.txt

5.4K

07_Distance_Measures_22-39_djvu.txt

3.2K

08_Nearest_Neighbor_Learning_11-39_djvu.txt

6.3K

09_Frequent_Itemsets_29-50_djvu.txt

2.3K

10_A-Priori_Algorithm_13-07_djvu.txt

4.1K

11_Improvements_to_A-Priori_17-26__Advanced_djvu.txt

4.3K

12_All_or_Most_Frequent_Itemsets_in_2_Passes_14-40_Advanced_djvu.txt

2.9K

01_Community_Detection_in_Graphs-_Motivation_5-44_djvu.txt

1.8K

02_The_Affiliation_Graph_Model_10-04_djvu.txt

1.7K

03_From_AGM_to_BIGCLAM_8-48_djvu.txt

2.4K

04_Solving_the_BIGCLAM_9-19_djvu.txt

2.0K

05_Detecting_Communities_as_Clusters_8-39_Advanced_djvu.txt

2.0K

06_What_Makes_a_Good_Cluster_8-48_Advanced_djvu.txt

1.8K

07_The_Graph_Laplacian_Matrix_6-51_Advanced_djvu.txt

986.0B

08_Examples_of_Eigendecompositions_of_Graphs_6-16_Advanced_djvu.txt

1.3K

09_Defining_the_Graph_Laplacian_3-27_Advanced_djvu.txt

2.1K

10_Spectral_Graph_Partitioning-_Finding_a_Partition_13-25_Advanced_djvu.txt

3.0K

11_Spectral_Clustering-_Three_Steps_7-17_Advanced_djvu.txt

4.2K

12_Analysis_of_Large_Graphs-_Trawling_9-02_Advanced_djvu.txt

2.5K

13_Mining_Data_Streams_12-01_djvu.txt

4.9K

14_Counting_1s_29-00_Advanced_djvu.txt

4.4K

15_Bloom_Filters_18-00_djvu.txt

3.4K

16_Sampling_a_Stream_11-30_djvu.txt

4.8K

17_Counting_Distinct_Elements_25-59_Advanced_djvu.txt

2.7K

01_Overview_of_Recommender_Systems_16-51_djvu.txt

3.5K

02_Content-Based_Recommendations_21-00_djvu.txt

5.3K

03_Collaborative_Filtering_20-52_djvu.txt

2.5K

04_Implementing_Collaborative_Filtering_13-46_Advanced_djvu.txt

1.0K

05_Evaluating_Recommender_Systems_6-09_djvu.txt

3.0K

06_Dimensionality_Reduction-_Introduction_12-01_djvu.txt

5.1K

07_Singular-Value_Decomposition_13-39_djvu.txt

5.8K

08_Dimensionality_Reduction_with_SVD_9-04_djvu.txt

2.7K

09_SVD_Gives_the_Best_Low-Rank_Approximation_8-28_Advanced_djvu.txt

4.4K

10_SVD_Example_and_Conclusion_11-58_djvu.txt

2.8K

11_CUR_Decomposition_6-27_Advanced_djvu.txt

1.5K

12_The_CUR_Algorithm_6-15_Advanced_djvu.txt

1.9K

13_Discussion_of_the_CUR_Method_7-09_djvu.txt

3.8K

14_Latent-Factor_Models_16-11_djvu.txt

7.1K

15_Latent-Factor_Recommender_System_14-16_djvu.txt

5.9K

16_Finding_the_Latent_Factors_13-20_djvu.txt

5.3K

17_Extension_to_Include_Global_Effects_9-42_Advanced_djvu.txt

2.9K

01_Overview_of_Clustering_8-46_djvu.txt

3.3K

02_Hierarchical_Clustering_14-07_djvu.txt

2.4K

03_The_k-Means_Algorithm_12-49_djvu.txt

5.3K

04_The_BFR_Algorithm_25-01_djvu.txt

1.7K

05_The_CURE_Algorithm_15-13_Advanced_djvu.txt

3.1K

06_Computational_Advertising-_Bipartite_Graph_Matching_24-47_djvu.txt

5.7K

07_The_AdWords_Problem_19-21_djvu.txt

3.4K

08_The_Balance_Algorithm_15-16_djvu.txt

2.0K

09_Generalized_Balance_14-35_Advanced_djvu.txt

1.4K

01_Support_Vector_Machines-_Introduction_7-30_djvu.txt

2.4K

02_Support_Vector_Machines-_Mathematical_Formulation_12-15_djvu.txt

1.4K

03_What_is_the_Margin_8-22_djvu.txt

1.5K

04_Soft-Margin_SVMs_9-46_djvu.txt

3.9K

05_How_to_Compute_the_Margin_14-36_Advanced_djvu.txt

2.8K

06_Support_Vector_Machines-_Example_7-07_djvu.txt

1.8K

07_Decision_Trees_8-33_djvu.txt

3.8K

08_How_to_Construct_a_Tree_13-21_djvu.txt

3.9K

09_Information_Gain_9-50_djvu.txt

4.4K

10_Building_Decision_Trees_Using_MapReduce_8-14_Advanced_djvu.txt

2.4K

11_Decision_Trees-_Conclusion_7-25_djvu.txt

2.9K

12_MapReduce_Algorithms_Part_I_10-51_Advanced_djvu.txt

4.1K

13_MapReduce_Algorithms_Part_II_9-46_Advanced_djvu.txt

5.8K

14_Theory_of_MapReduce_Algorithms_19-39_Advanced_djvu.txt

6.5K

15_Matrix_Multiplication_in_MapReduce_24-48_Advanced_djvu.txt

5.1K

01_LSH_Families_21-13_djvu.txt

2.9K

02_More_About_LSH_Families_12-57_djvu.txt

2.1K

03_Sets_and_Strings_With_a_High_Degree_of_Similarity_11-29_Advanced_djvu.txt

1.4K

04_Prefix_of_a_String_7-43_Advanced_djvu.txt

2.2K

05_Positions_Within_Prefixes_14-04_Advanced_djvu.txt

2.8K

06_Exploiting_Length_14-39_Advanced_djvu.txt

3.8K

07_Computing_PageRank_on_Big_Graphs_10-18_Advanced_djvu.txt

3.1K

08_Topic-Specific_PageRank_10-06_djvu.txt

2.0K

09_Application_to_Measuring_Proximity_in_Graphs_6-25_djvu.txt

5.7K

10_Hubs_and_Authorities_15-16_Advanced_djvu.txt

4.4K

11_Web_Spam-_Introduction_6-50_djvu.txt

2.5K

12_Spam_Farms_8-00_djvu.txt

3.5K

13_TrustRank_10-05_djvu.txt

30 files

HTML

BACK

68.7K

Announcements.html

59.7K

DiscussionForums.html

37.7K

Final Exam.html

85.4K

0_Final_Basic.html

68.0K

1_Final_Advanced.html

40.2K

GradingandLogistics.html

56.1K

QuickQuestions15.html

94.2K

Quizzes (Homeworks).html

47.1K

0_Week_1_Basic.html

48.4K

10_Week6A_Advanced.html

47.8K

11_Week6B_Basic.html

49.2K

12_Week7A_Advanced.html

43.9K

13_Week7B_Basic.html

42.5K

zip_page.html

41.6K

15_PageRank_Optional_programming_assignment.html

50.2K

1_Week_2A_LSH_Basic.html

47.2K

2_Week_2B_Frequent_Itemsets_Basic.html

45.2K

3_Week_2C_Advanced.html

51.5K

4_Week3A_Advanced.html

44.1K

5_Week3B_Basic.html

43.9K

6_Week4A_Basic.html

47.7K

7_Week4B_Basic.html

49.0K

8_Week5A_Advanced.html

50.9K

9_Week5B_Basic.html

43.1K

Syllabus.html

37.7K

VideoErrata.html

32.6K

assignment_home.html

68.8K

course_home.html

1.3M

entered_login.html

1 file

ITEM TILE

94 files

MPEG4

BACK

27.6M

01_Distributed_File_Systems_15-50.mp4

35.7M

02_The_MapReduce_Computational_Model_22-04.mp4

20.2M

03_Scheduling_and_Data_Flow_12-43.mp4

19.1M

04_Combiners_and_Partition_Functions_12-17_Advanced.mp4

14.7M

05_Link_Analysis_and_PageRank_9-39.mp4

13.8M

06_PageRank-_The_Flow_Formulation_9-16.mp4

12.6M

07_PageRank-_The_Matrix_Formulation_8-02.mp4

16.2M

08_PageRank-_Power_Iteration_10-34.mp4

18.4M

09_PageRank-_The_Google_Formulation_12-08.mp4

18.7M

10_Why_Teleports_Solve_the_Problem_12-26.mp4

20.1M

11_How_we_Really_Compute_PageRank_13-49.mp4

20.2M

01_Finding_Similar_Sets_13-37.mp4

41.3M

02_Minhashing_25-18.mp4

32.0M

03_Locality-Sensitive_Hashing_19-24.mp4

18.9M

04_Applications_of_LSH_11-40.mp4

10.9M

05_Fingerprint_Matching_7-07.mp4

9.5M

06_Finding_Duplicate_News_Articles_6-08.mp4

34.5M

07_Distance_Measures_22-39.mp4

19.1M

08_Nearest_Neighbor_Learning_11-39.mp4

51.7M

09_Frequent_Itemsets_29-50.mp4

21.7M

10_A-Priori_Algorithm_13-07.mp4

28.2M

11_Improvements_to_A-Priori_17-26__Advanced.mp4

22.5M

12_All_or_Most_Frequent_Itemsets_in_2_Passes_14-40_Advanced.mp4

8.5M

01_Community_Detection_in_Graphs-_Motivation_5-44.mp4

14.8M

02_The_Affiliation_Graph_Model_10-04.mp4

13.4M

03_From_AGM_to_BIGCLAM_8-48.mp4

15.1M

04_Solving_the_BIGCLAM_9-19.mp4

14.5M

05_Detecting_Communities_as_Clusters_8-39_Advanced.mp4

13.6M

06_What_Makes_a_Good_Cluster_8-48_Advanced.mp4

10.0M

07_The_Graph_Laplacian_Matrix_6-51_Advanced.mp4

9.3M

08_Examples_of_Eigendecompositions_of_Graphs_6-16_Advanced.mp4

5.2M

09_Defining_the_Graph_Laplacian_3-27_Advanced.mp4

18.8M

10_Spectral_Graph_Partitioning-_Finding_a_Partition_13-25_Advanced.mp4

10.4M

11_Spectral_Clustering-_Three_Steps_7-17_Advanced.mp4

14.1M

12_Analysis_of_Large_Graphs-_Trawling_9-02_Advanced.mp4

18.9M

13_Mining_Data_Streams_12-01.mp4

44.1M

14_Counting_1s_29-00_Advanced.mp4

28.4M

15_Bloom_Filters_18-00.mp4

17.6M

16_Sampling_a_Stream_11-30.mp4

37.7M

17_Counting_Distinct_Elements_25-59_Advanced.mp4

29.0M

01_Overview_of_Recommender_Systems_16-51.mp4

34.1M

02_Content-Based_Recommendations_21-00.mp4

29.2M

03_Collaborative_Filtering_20-52.mp4

20.0M

04_Implementing_Collaborative_Filtering_13-46_Advanced.mp4

9.3M

05_Evaluating_Recommender_Systems_6-09.mp4

18.4M

06_Dimensionality_Reduction-_Introduction_12-01.mp4

19.3M

07_Singular-Value_Decomposition_13-39.mp4

12.6M

08_Dimensionality_Reduction_with_SVD_9-04.mp4

12.3M

09_SVD_Gives_the_Best_Low-Rank_Approximation_8-28_Advanced.mp4

17.8M

10_SVD_Example_and_Conclusion_11-58.mp4

8.9M

11_CUR_Decomposition_6-27_Advanced.mp4

8.8M

12_The_CUR_Algorithm_6-15_Advanced.mp4

10.4M

13_Discussion_of_the_CUR_Method_7-09.mp4

23.8M

14_Latent-Factor_Models_16-11.mp4

19.4M

15_Latent-Factor_Recommender_System_14-16.mp4

20.1M

16_Finding_the_Latent_Factors_13-20.mp4

13.8M

17_Extension_to_Include_Global_Effects_9-42_Advanced.mp4

15.4M

01_Overview_of_Clustering_8-46.mp4

22.5M

02_Hierarchical_Clustering_14-07.mp4

21.6M

03_The_k-Means_Algorithm_12-49.mp4

39.6M

04_The_BFR_Algorithm_25-01.mp4

24.6M

05_The_CURE_Algorithm_15-13_Advanced.mp4

43.4M

06_Computational_Advertising-_Bipartite_Graph_Matching_24-47.mp4

31.6M

07_The_AdWords_Problem_19-21.mp4

22.1M

08_The_Balance_Algorithm_15-16.mp4

20.4M

09_Generalized_Balance_14-35_Advanced.mp4

11.5M

01_Support_Vector_Machines-_Introduction_7-30.mp4

16.7M

02_Support_Vector_Machines-_Mathematical_Formulation_12-15.mp4

12.9M

03_What_is_the_Margin_8-22.mp4

13.6M

04_Soft-Margin_SVMs_9-46.mp4

22.8M

05_How_to_Compute_the_Margin_14-36_Advanced.mp4

11.3M

06_Support_Vector_Machines-_Example_7-07.mp4

13.9M

07_Decision_Trees_8-33.mp4

22.2M

08_How_to_Construct_a_Tree_13-21.mp4

15.1M

09_Information_Gain_9-50.mp4

13.6M

10_Building_Decision_Trees_Using_MapReduce_8-14_Advanced.mp4

11.4M

11_Decision_Trees-_Conclusion_7-25.mp4

14.8M

12_MapReduce_Algorithms_Part_I_10-51_Advanced.mp4

13.1M

13_MapReduce_Algorithms_Part_II_9-46_Advanced.mp4

26.0M

14_Theory_of_MapReduce_Algorithms_19-39_Advanced.mp4

34.5M

15_Matrix_Multiplication_in_MapReduce_24-48_Advanced.mp4

34.0M

01_LSH_Families_21-13.mp4

19.9M

02_More_About_LSH_Families_12-57.mp4

17.5M

03_Sets_and_Strings_With_a_High_Degree_of_Similarity_11-29_Advanced.mp4

12.6M

04_Prefix_of_a_String_7-43_Advanced.mp4

22.7M

05_Positions_Within_Prefixes_14-04_Advanced.mp4

23.9M

06_Exploiting_Length_14-39_Advanced.mp4

15.6M

07_Computing_PageRank_on_Big_Graphs_10-18_Advanced.mp4

15.7M

08_Topic-Specific_PageRank_10-06.mp4

9.9M

09_Application_to_Measuring_Proximity_in_Graphs_6-25.mp4

22.1M

10_Hubs_and_Authorities_15-16_Advanced.mp4

11.0M

11_Web_Spam-_Introduction_6-50.mp4

12.2M

12_Spam_Farms_8-00.mp4

15.4M

13_TrustRank_10-05.mp4

94 files

OGG VIDEO

BACK

67.5M

01_Distributed_File_Systems_15-50.ogv

94.5M

02_The_MapReduce_Computational_Model_22-04.ogv

54.3M

03_Scheduling_and_Data_Flow_12-43.ogv

52.6M

04_Combiners_and_Partition_Functions_12-17_Advanced.ogv

41.2M

05_Link_Analysis_and_PageRank_9-39.ogv

39.6M

06_PageRank-_The_Flow_Formulation_9-16.ogv

34.4M

07_PageRank-_The_Matrix_Formulation_8-02.ogv

45.2M

08_PageRank-_Power_Iteration_10-34.ogv

51.5M

09_PageRank-_The_Google_Formulation_12-08.ogv

53.0M

10_Why_Teleports_Solve_the_Problem_12-26.ogv

59.8M

11_How_we_Really_Compute_PageRank_13-49.ogv

57.5M

01_Finding_Similar_Sets_13-37.ogv

108.0M

02_Minhashing_25-18.ogv

82.1M

03_Locality-Sensitive_Hashing_19-24.ogv

49.3M

04_Applications_of_LSH_11-40.ogv

29.9M

05_Fingerprint_Matching_7-07.ogv

25.8M

06_Finding_Duplicate_News_Articles_6-08.ogv

96.2M

07_Distance_Measures_22-39.ogv

49.6M

08_Nearest_Neighbor_Learning_11-39.ogv

126.8M

09_Frequent_Itemsets_29-50.ogv

56.0M

10_A-Priori_Algorithm_13-07.ogv

74.5M

11_Improvements_to_A-Priori_17-26__Advanced.ogv

62.5M

12_All_or_Most_Frequent_Itemsets_in_2_Passes_14-40_Advanced.ogv

24.6M

01_Community_Detection_in_Graphs-_Motivation_5-44.ogv

43.2M

02_The_Affiliation_Graph_Model_10-04.ogv

37.5M

03_From_AGM_to_BIGCLAM_8-48.ogv

39.8M

04_Solving_the_BIGCLAM_9-19.ogv

36.7M

05_Detecting_Communities_as_Clusters_8-39_Advanced.ogv

37.3M

06_What_Makes_a_Good_Cluster_8-48_Advanced.ogv

29.1M

07_The_Graph_Laplacian_Matrix_6-51_Advanced.ogv

26.8M

08_Examples_of_Eigendecompositions_of_Graphs_6-16_Advanced.ogv

14.8M

09_Defining_the_Graph_Laplacian_3-27_Advanced.ogv

56.6M

10_Spectral_Graph_Partitioning-_Finding_a_Partition_13-25_Advanced.ogv

31.0M

11_Spectral_Clustering-_Three_Steps_7-17_Advanced.ogv

38.3M

12_Analysis_of_Large_Graphs-_Trawling_9-02_Advanced.ogv

50.7M

13_Mining_Data_Streams_12-01.ogv

122.0M

14_Counting_1s_29-00_Advanced.ogv

76.4M

15_Bloom_Filters_18-00.ogv

48.6M

16_Sampling_a_Stream_11-30.ogv

110.1M

17_Counting_Distinct_Elements_25-59_Advanced.ogv

71.4M

01_Overview_of_Recommender_Systems_16-51.ogv

88.9M

02_Content-Based_Recommendations_21-00.ogv

88.6M

03_Collaborative_Filtering_20-52.ogv

58.3M

04_Implementing_Collaborative_Filtering_13-46_Advanced.ogv

25.6M

05_Evaluating_Recommender_Systems_6-09.ogv

52.0M

06_Dimensionality_Reduction-_Introduction_12-01.ogv

58.1M

07_Singular-Value_Decomposition_13-39.ogv

38.8M

08_Dimensionality_Reduction_with_SVD_9-04.ogv

36.4M

09_SVD_Gives_the_Best_Low-Rank_Approximation_8-28_Advanced.ogv

51.5M

10_SVD_Example_and_Conclusion_11-58.ogv

27.4M

11_CUR_Decomposition_6-27_Advanced.ogv

26.6M

12_The_CUR_Algorithm_6-15_Advanced.ogv

30.7M

13_Discussion_of_the_CUR_Method_7-09.ogv

69.8M

14_Latent-Factor_Models_16-11.ogv

61.2M

15_Latent-Factor_Recommender_System_14-16.ogv

57.3M

16_Finding_the_Latent_Factors_13-20.ogv

41.9M

17_Extension_to_Include_Global_Effects_9-42_Advanced.ogv

37.4M

01_Overview_of_Clustering_8-46.ogv

60.3M

02_Hierarchical_Clustering_14-07.ogv

55.4M

03_The_k-Means_Algorithm_12-49.ogv

108.2M

04_The_BFR_Algorithm_25-01.ogv

65.7M

05_The_CURE_Algorithm_15-13_Advanced.ogv

107.0M

06_Computational_Advertising-_Bipartite_Graph_Matching_24-47.ogv

83.1M

07_The_AdWords_Problem_19-21.ogv

65.2M

08_The_Balance_Algorithm_15-16.ogv

61.4M

09_Generalized_Balance_14-35_Advanced.ogv

31.9M

01_Support_Vector_Machines-_Introduction_7-30.ogv

52.0M

02_Support_Vector_Machines-_Mathematical_Formulation_12-15.ogv

35.7M

03_What_is_the_Margin_8-22.ogv

41.6M

04_Soft-Margin_SVMs_9-46.ogv

62.6M

05_How_to_Compute_the_Margin_14-36_Advanced.ogv

30.6M

06_Support_Vector_Machines-_Example_7-07.ogv

36.5M

07_Decision_Trees_8-33.ogv

57.1M

08_How_to_Construct_a_Tree_13-21.ogv

42.0M

09_Information_Gain_9-50.ogv

35.1M

10_Building_Decision_Trees_Using_MapReduce_8-14_Advanced.ogv

31.5M

11_Decision_Trees-_Conclusion_7-25.ogv

45.9M

12_MapReduce_Algorithms_Part_I_10-51_Advanced.ogv

40.8M

13_MapReduce_Algorithms_Part_II_9-46_Advanced.ogv

83.4M

14_Theory_of_MapReduce_Algorithms_19-39_Advanced.ogv

105.4M

15_Matrix_Multiplication_in_MapReduce_24-48_Advanced.ogv

90.3M

01_LSH_Families_21-13.ogv

55.0M

02_More_About_LSH_Families_12-57.ogv

48.8M

03_Sets_and_Strings_With_a_High_Degree_of_Similarity_11-29_Advanced.ogv

32.7M

04_Prefix_of_a_String_7-43_Advanced.ogv

59.8M

05_Positions_Within_Prefixes_14-04_Advanced.ogv

62.2M

06_Exploiting_Length_14-39_Advanced.ogv

44.2M

07_Computing_PageRank_on_Big_Graphs_10-18_Advanced.ogv

43.6M

08_Topic-Specific_PageRank_10-06.ogv

27.6M

09_Application_to_Measuring_Proximity_in_Graphs_6-25.ogv

65.4M

10_Hubs_and_Authorities_15-16_Advanced.ogv

29.3M

11_Web_Spam-_Introduction_6-50.ogv

34.2M

12_Spam_Farms_8-00.ogv

43.2M

13_TrustRank_10-05.ogv

94 files

PDF

BACK

1.6M

01_Distributed_File_Systems_15-50.pdf

1.3M

02_The_MapReduce_Computational_Model_22-04.pdf

824.9K

03_Scheduling_and_Data_Flow_12-43.pdf

1,008.4K

04_Combiners_and_Partition_Functions_12-17_Advanced.pdf

1.7M

05_Link_Analysis_and_PageRank_9-39.pdf

777.9K

06_PageRank-_The_Flow_Formulation_9-16.pdf

336.5K

07_PageRank-_The_Matrix_Formulation_8-02.pdf

387.1K

08_PageRank-_Power_Iteration_10-34.pdf

891.0K

09_PageRank-_The_Google_Formulation_12-08.pdf

530.3K

10_Why_Teleports_Solve_the_Problem_12-26.pdf

989.8K

11_How_we_Really_Compute_PageRank_13-49.pdf

560.9K

01_Finding_Similar_Sets_13-37.pdf

961.0K

02_Minhashing_25-18.pdf

1.1M

03_Locality-Sensitive_Hashing_19-24.pdf

771.1K

04_Applications_of_LSH_11-40.pdf

637.3K

05_Fingerprint_Matching_7-07.pdf

533.8K

06_Finding_Duplicate_News_Articles_6-08.pdf

1.6M

07_Distance_Measures_22-39.pdf

833.2K

08_Nearest_Neighbor_Learning_11-39.pdf

1.4M

09_Frequent_Itemsets_29-50.pdf

651.0K

10_A-Priori_Algorithm_13-07.pdf

1.0M

11_Improvements_to_A-Priori_17-26__Advanced.pdf

1.1M

12_All_or_Most_Frequent_Itemsets_in_2_Passes_14-40_Advanced.pdf

1.4M

01_Community_Detection_in_Graphs-_Motivation_5-44.pdf

1.4M

02_The_Affiliation_Graph_Model_10-04.pdf

585.7K

03_From_AGM_to_BIGCLAM_8-48.pdf

377.7K

04_Solving_the_BIGCLAM_9-19.pdf

1.1M

05_Detecting_Communities_as_Clusters_8-39_Advanced.pdf

438.6K

06_What_Makes_a_Good_Cluster_8-48_Advanced.pdf

764.5K

07_The_Graph_Laplacian_Matrix_6-51_Advanced.pdf

263.5K

08_Examples_of_Eigendecompositions_of_Graphs_6-16_Advanced.pdf

216.1K

09_Defining_the_Graph_Laplacian_3-27_Advanced.pdf

749.4K

10_Spectral_Graph_Partitioning-_Finding_a_Partition_13-25_Advanced.pdf

503.2K

11_Spectral_Clustering-_Three_Steps_7-17_Advanced.pdf

860.1K

12_Analysis_of_Large_Graphs-_Trawling_9-02_Advanced.pdf

489.4K

13_Mining_Data_Streams_12-01.pdf

801.2K

14_Counting_1s_29-00_Advanced.pdf

830.8K

15_Bloom_Filters_18-00.pdf

707.2K

16_Sampling_a_Stream_11-30.pdf

992.2K

17_Counting_Distinct_Elements_25-59_Advanced.pdf

1.3M

01_Overview_of_Recommender_Systems_16-51.pdf

1.1M

02_Content-Based_Recommendations_21-00.pdf

1.4M

03_Collaborative_Filtering_20-52.pdf

880.1K

04_Implementing_Collaborative_Filtering_13-46_Advanced.pdf

560.6K

05_Evaluating_Recommender_Systems_6-09.pdf

1,015.1K

06_Dimensionality_Reduction-_Introduction_12-01.pdf

505.9K

07_Singular-Value_Decomposition_13-39.pdf

622.4K

08_Dimensionality_Reduction_with_SVD_9-04.pdf

368.0K

09_SVD_Gives_the_Best_Low-Rank_Approximation_8-28_Advanced.pdf

729.0K

10_SVD_Example_and_Conclusion_11-58.pdf

839.1K

11_CUR_Decomposition_6-27_Advanced.pdf

327.5K

12_The_CUR_Algorithm_6-15_Advanced.pdf

305.1K

13_Discussion_of_the_CUR_Method_7-09.pdf

937.2K

14_Latent-Factor_Models_16-11.pdf

997.1K

15_Latent-Factor_Recommender_System_14-16.pdf

886.1K

16_Finding_the_Latent_Factors_13-20.pdf

1.5M

17_Extension_to_Include_Global_Effects_9-42_Advanced.pdf

1.1M

01_Overview_of_Clustering_8-46.pdf

876.3K

02_Hierarchical_Clustering_14-07.pdf

1.1M

03_The_k-Means_Algorithm_12-49.pdf

1.7M

04_The_BFR_Algorithm_25-01.pdf

996.2K

05_The_CURE_Algorithm_15-13_Advanced.pdf

1.5M

06_Computational_Advertising-_Bipartite_Graph_Matching_24-47.pdf

1.4M

07_The_AdWords_Problem_19-21.pdf

1,006.8K

08_The_Balance_Algorithm_15-16.pdf

801.2K

09_Generalized_Balance_14-35_Advanced.pdf

672.8K

01_Support_Vector_Machines-_Introduction_7-30.pdf

469.9K

02_Support_Vector_Machines-_Mathematical_Formulation_12-15.pdf

741.5K

03_What_is_the_Margin_8-22.pdf

259.2K

04_Soft-Margin_SVMs_9-46.pdf

797.4K

05_How_to_Compute_the_Margin_14-36_Advanced.pdf

539.2K

06_Support_Vector_Machines-_Example_7-07.pdf

734.5K

07_Decision_Trees_8-33.pdf

550.7K

08_How_to_Construct_a_Tree_13-21.pdf

283.7K

09_Information_Gain_9-50.pdf

690.2K

10_Building_Decision_Trees_Using_MapReduce_8-14_Advanced.pdf

543.7K

11_Decision_Trees-_Conclusion_7-25.pdf

686.3K

12_MapReduce_Algorithms_Part_I_10-51_Advanced.pdf

581.0K

13_MapReduce_Algorithms_Part_II_9-46_Advanced.pdf

1.0M

14_Theory_of_MapReduce_Algorithms_19-39_Advanced.pdf

1.3M

15_Matrix_Multiplication_in_MapReduce_24-48_Advanced.pdf

1.5M

01_LSH_Families_21-13.pdf

990.3K

02_More_About_LSH_Families_12-57.pdf

604.7K

03_Sets_and_Strings_With_a_High_Degree_of_Similarity_11-29_Advanced.pdf

352.3K

04_Prefix_of_a_String_7-43_Advanced.pdf

590.5K

05_Positions_Within_Prefixes_14-04_Advanced.pdf

594.2K

06_Exploiting_Length_14-39_Advanced.pdf

449.8K

07_Computing_PageRank_on_Big_Graphs_10-18_Advanced.pdf

710.3K

08_Topic-Specific_PageRank_10-06.pdf

727.5K

09_Application_to_Measuring_Proximity_in_Graphs_6-25.pdf

950.8K

10_Hubs_and_Authorities_15-16_Advanced.pdf

660.2K

11_Web_Spam-_Introduction_6-50.pdf

363.6K

12_Spam_Farms_8-00.pdf

748.7K

13_TrustRank_10-05.pdf

94 files

SINGLE PAGE PROCESSED JP2 ZIP

BACK

4.3M

01_Distributed_File_Systems_15-50_jp2.zip

4.3M

02_The_MapReduce_Computational_Model_22-04_jp2.zip

3.1M

03_Scheduling_and_Data_Flow_12-43_jp2.zip

4.2M

04_Combiners_and_Partition_Functions_12-17_Advanced_jp2.zip

8.1M

05_Link_Analysis_and_PageRank_9-39_jp2.zip

3.0M

06_PageRank-_The_Flow_Formulation_9-16_jp2.zip

1.8M

07_PageRank-_The_Matrix_Formulation_8-02_jp2.zip

3.2M

08_PageRank-_Power_Iteration_10-34_jp2.zip

3.6M

09_PageRank-_The_Google_Formulation_12-08_jp2.zip

3.7M

10_Why_Teleports_Solve_the_Problem_12-26_jp2.zip

3.3M

11_How_we_Really_Compute_PageRank_13-49_jp2.zip

3.5M

01_Finding_Similar_Sets_13-37_jp2.zip

6.0M

02_Minhashing_25-18_jp2.zip

5.3M

03_Locality-Sensitive_Hashing_19-24_jp2.zip

3.9M

04_Applications_of_LSH_11-40_jp2.zip

3.0M

05_Fingerprint_Matching_7-07_jp2.zip

2.9M

06_Finding_Duplicate_News_Articles_6-08_jp2.zip

7.4M

07_Distance_Measures_22-39_jp2.zip

4.0M

08_Nearest_Neighbor_Learning_11-39_jp2.zip

8.5M

09_Frequent_Itemsets_29-50_jp2.zip

3.2M

10_A-Priori_Algorithm_13-07_jp2.zip

5.6M

11_Improvements_to_A-Priori_17-26__Advanced_jp2.zip

6.0M

12_All_or_Most_Frequent_Itemsets_in_2_Passes_14-40_Advanced_jp2.zip

4.8M

01_Community_Detection_in_Graphs-_Motivation_5-44_jp2.zip

3.7M

02_The_Affiliation_Graph_Model_10-04_jp2.zip

2.1M

03_From_AGM_to_BIGCLAM_8-48_jp2.zip

3.0M

04_Solving_the_BIGCLAM_9-19_jp2.zip

4.8M

05_Detecting_Communities_as_Clusters_8-39_Advanced_jp2.zip

3.0M

06_What_Makes_a_Good_Cluster_8-48_Advanced_jp2.zip

2.5M

07_The_Graph_Laplacian_Matrix_6-51_Advanced_jp2.zip

1.1M

08_Examples_of_Eigendecompositions_of_Graphs_6-16_Advanced_jp2.zip

1.4M

09_Defining_the_Graph_Laplacian_3-27_Advanced_jp2.zip

2.6M

10_Spectral_Graph_Partitioning-_Finding_a_Partition_13-25_Advanced_jp2.zip

3.5M

11_Spectral_Clustering-_Three_Steps_7-17_Advanced_jp2.zip

5.1M

12_Analysis_of_Large_Graphs-_Trawling_9-02_Advanced_jp2.zip

3.6M

13_Mining_Data_Streams_12-01_jp2.zip

6.8M

14_Counting_1s_29-00_Advanced_jp2.zip

4.6M

15_Bloom_Filters_18-00_jp2.zip

3.7M

16_Sampling_a_Stream_11-30_jp2.zip

5.8M

17_Counting_Distinct_Elements_25-59_Advanced_jp2.zip

3.9M

01_Overview_of_Recommender_Systems_16-51_jp2.zip

4.8M

02_Content-Based_Recommendations_21-00_jp2.zip

5.5M

03_Collaborative_Filtering_20-52_jp2.zip

3.3M

04_Implementing_Collaborative_Filtering_13-46_Advanced_jp2.zip

1.5M

05_Evaluating_Recommender_Systems_6-09_jp2.zip

4.5M

06_Dimensionality_Reduction-_Introduction_12-01_jp2.zip

5.3M

07_Singular-Value_Decomposition_13-39_jp2.zip

6.1M

08_Dimensionality_Reduction_with_SVD_9-04_jp2.zip

2.9M

09_SVD_Gives_the_Best_Low-Rank_Approximation_8-28_Advanced_jp2.zip

4.5M

10_SVD_Example_and_Conclusion_11-58_jp2.zip

3.5M

11_CUR_Decomposition_6-27_Advanced_jp2.zip

1.8M

12_The_CUR_Algorithm_6-15_Advanced_jp2.zip

2.1M

13_Discussion_of_the_CUR_Method_7-09_jp2.zip

4.8M

14_Latent-Factor_Models_16-11_jp2.zip

7.1M

15_Latent-Factor_Recommender_System_14-16_jp2.zip

6.6M

16_Finding_the_Latent_Factors_13-20_jp2.zip

7.2M

17_Extension_to_Include_Global_Effects_9-42_Advanced_jp2.zip

4.1M

01_Overview_of_Clustering_8-46_jp2.zip

4.8M

02_Hierarchical_Clustering_14-07_jp2.zip

3.6M

03_The_k-Means_Algorithm_12-49_jp2.zip

7.8M

04_The_BFR_Algorithm_25-01_jp2.zip

3.4M

05_The_CURE_Algorithm_15-13_Advanced_jp2.zip

5.2M

06_Computational_Advertising-_Bipartite_Graph_Matching_24-47_jp2.zip

5.0M

07_The_AdWords_Problem_19-21_jp2.zip

4.3M

08_The_Balance_Algorithm_15-16_jp2.zip

2.5M

09_Generalized_Balance_14-35_Advanced_jp2.zip

1.9M

01_Support_Vector_Machines-_Introduction_7-30_jp2.zip

3.2M

02_Support_Vector_Machines-_Mathematical_Formulation_12-15_jp2.zip

2.7M

03_What_is_the_Margin_8-22_jp2.zip

2.0M

04_Soft-Margin_SVMs_9-46_jp2.zip

5.0M

05_How_to_Compute_the_Margin_14-36_Advanced_jp2.zip

3.3M

06_Support_Vector_Machines-_Example_7-07_jp2.zip

2.5M

07_Decision_Trees_8-33_jp2.zip

5.4M

08_How_to_Construct_a_Tree_13-21_jp2.zip

4.2M

09_Information_Gain_9-50_jp2.zip

5.2M

10_Building_Decision_Trees_Using_MapReduce_8-14_Advanced_jp2.zip

2.6M

11_Decision_Trees-_Conclusion_7-25_jp2.zip

3.6M

12_MapReduce_Algorithms_Part_I_10-51_Advanced_jp2.zip

1.9M

13_MapReduce_Algorithms_Part_II_9-46_Advanced_jp2.zip

6.5M

14_Theory_of_MapReduce_Algorithms_19-39_Advanced_jp2.zip

6.6M

15_Matrix_Multiplication_in_MapReduce_24-48_Advanced_jp2.zip

6.5M

01_LSH_Families_21-13_jp2.zip

3.7M

02_More_About_LSH_Families_12-57_jp2.zip

3.1M

03_Sets_and_Strings_With_a_High_Degree_of_Similarity_11-29_Advanced_jp2.zip

1.8M

04_Prefix_of_a_String_7-43_Advanced_jp2.zip

2.7M

05_Positions_Within_Prefixes_14-04_Advanced_jp2.zip

3.6M

06_Exploiting_Length_14-39_Advanced_jp2.zip

4.0M

07_Computing_PageRank_on_Big_Graphs_10-18_Advanced_jp2.zip

4.0M

08_Topic-Specific_PageRank_10-06_jp2.zip

3.3M

09_Application_to_Measuring_Proximity_in_Graphs_6-25_jp2.zip

7.4M

10_Hubs_and_Authorities_15-16_Advanced_jp2.zip

4.8M

11_Web_Spam-_Introduction_6-50_jp2.zip

3.7M

12_Spam_Farms_8-00_jp2.zip

4.4M

13_TrustRank_10-05_jp2.zip

94 files

SUBRIP

BACK

24.2K

01_Distributed_File_Systems_15-50.srt

29.8K

02_The_MapReduce_Computational_Model_22-04.srt

17.1K

03_Scheduling_and_Data_Flow_12-43.srt

15.3K

04_Combiners_and_Partition_Functions_12-17_Advanced.srt

15.3K

05_Link_Analysis_and_PageRank_9-39.srt

14.0K

06_PageRank-_The_Flow_Formulation_9-16.srt

11.3K

07_PageRank-_The_Matrix_Formulation_8-02.srt

14.7K

08_PageRank-_Power_Iteration_10-34.srt

17.5K

09_PageRank-_The_Google_Formulation_12-08.srt

17.0K

10_Why_Teleports_Solve_the_Problem_12-26.srt

20.2K

11_How_we_Really_Compute_PageRank_13-49.srt

18.5K

01_Finding_Similar_Sets_13-37.srt

30.5K

02_Minhashing_25-18.srt

25.1K

03_Locality-Sensitive_Hashing_19-24.srt

16.9K

04_Applications_of_LSH_11-40.srt

9.6K

05_Fingerprint_Matching_7-07.srt

8.9K

06_Finding_Duplicate_News_Articles_6-08.srt

30.3K

07_Distance_Measures_22-39.srt

17.2K

08_Nearest_Neighbor_Learning_11-39.srt

37.9K

09_Frequent_Itemsets_29-50.srt

16.9K

10_A-Priori_Algorithm_13-07.srt

24.2K

11_Improvements_to_A-Priori_17-26__Advanced.srt

20.7K

12_All_or_Most_Frequent_Itemsets_in_2_Passes_14-40_Advanced.srt

9.3K

01_Community_Detection_in_Graphs-_Motivation_5-44.srt

16.1K

02_The_Affiliation_Graph_Model_10-04.srt

13.2K

03_From_AGM_to_BIGCLAM_8-48.srt

13.8K

04_Solving_the_BIGCLAM_9-19.srt

13.5K

05_Detecting_Communities_as_Clusters_8-39_Advanced.srt

13.8K

06_What_Makes_a_Good_Cluster_8-48_Advanced.srt

10.7K

07_The_Graph_Laplacian_Matrix_6-51_Advanced.srt

9.6K

08_Examples_of_Eigendecompositions_of_Graphs_6-16_Advanced.srt

4.8K

09_Defining_the_Graph_Laplacian_3-27_Advanced.srt

19.7K

10_Spectral_Graph_Partitioning-_Finding_a_Partition_13-25_Advanced.srt

10.9K

11_Spectral_Clustering-_Three_Steps_7-17_Advanced.srt

12.5K

12_Analysis_of_Large_Graphs-_Trawling_9-02_Advanced.srt

16.1K

13_Mining_Data_Streams_12-01.srt

33.7K

14_Counting_1s_29-00_Advanced.srt

20.9K

15_Bloom_Filters_18-00.srt

16.3K

16_Sampling_a_Stream_11-30.srt

32.6K

17_Counting_Distinct_Elements_25-59_Advanced.srt

26.1K

01_Overview_of_Recommender_Systems_16-51.srt

27.9K

02_Content-Based_Recommendations_21-00.srt

28.2K

03_Collaborative_Filtering_20-52.srt

18.7K

04_Implementing_Collaborative_Filtering_13-46_Advanced.srt

8.2K

05_Evaluating_Recommender_Systems_6-09.srt

18.9K

06_Dimensionality_Reduction-_Introduction_12-01.srt

20.5K

07_Singular-Value_Decomposition_13-39.srt

13.4K

08_Dimensionality_Reduction_with_SVD_9-04.srt

11.9K

09_SVD_Gives_the_Best_Low-Rank_Approximation_8-28_Advanced.srt

16.9K

10_SVD_Example_and_Conclusion_11-58.srt

9.1K

11_CUR_Decomposition_6-27_Advanced.srt

8.9K

12_The_CUR_Algorithm_6-15_Advanced.srt

10.6K

13_Discussion_of_the_CUR_Method_7-09.srt

23.3K

14_Latent-Factor_Models_16-11.srt

20.1K

15_Latent-Factor_Recommender_System_14-16.srt

19.4K

16_Finding_the_Latent_Factors_13-20.srt

12.9K

17_Extension_to_Include_Global_Effects_9-42_Advanced.srt

12.7K

01_Overview_of_Clustering_8-46.srt

18.9K

02_Hierarchical_Clustering_14-07.srt

19.1K

03_The_k-Means_Algorithm_12-49.srt

34.9K

04_The_BFR_Algorithm_25-01.srt

22.5K

05_The_CURE_Algorithm_15-13_Advanced.srt

33.0K

06_Computational_Advertising-_Bipartite_Graph_Matching_24-47.srt

27.5K

07_The_AdWords_Problem_19-21.srt

21.4K

08_The_Balance_Algorithm_15-16.srt

18.2K

09_Generalized_Balance_14-35_Advanced.srt

10.4K

01_Support_Vector_Machines-_Introduction_7-30.srt

17.7K

02_Support_Vector_Machines-_Mathematical_Formulation_12-15.srt

11.2K

03_What_is_the_Margin_8-22.srt

14.1K

04_Soft-Margin_SVMs_9-46.srt

20.4K

05_How_to_Compute_the_Margin_14-36_Advanced.srt

10.3K

06_Support_Vector_Machines-_Example_7-07.srt

12.5K

07_Decision_Trees_8-33.srt

20.3K

08_How_to_Construct_a_Tree_13-21.srt

13.8K

09_Information_Gain_9-50.srt

12.0K

10_Building_Decision_Trees_Using_MapReduce_8-14_Advanced.srt

10.8K

11_Decision_Trees-_Conclusion_7-25.srt

15.2K

12_MapReduce_Algorithms_Part_I_10-51_Advanced.srt

12.9K

13_MapReduce_Algorithms_Part_II_9-46_Advanced.srt

26.8K

14_Theory_of_MapReduce_Algorithms_19-39_Advanced.srt

29.8K

15_Matrix_Multiplication_in_MapReduce_24-48_Advanced.srt

25.8K

01_LSH_Families_21-13.srt

16.9K

02_More_About_LSH_Families_12-57.srt

14.0K

03_Sets_and_Strings_With_a_High_Degree_of_Similarity_11-29_Advanced.srt

8.2K

04_Prefix_of_a_String_7-43_Advanced.srt

15.7K

05_Positions_Within_Prefixes_14-04_Advanced.srt

18.0K

06_Exploiting_Length_14-39_Advanced.srt

15.4K

07_Computing_PageRank_on_Big_Graphs_10-18_Advanced.srt

14.9K

08_Topic-Specific_PageRank_10-06.srt

9.9K

09_Application_to_Measuring_Proximity_in_Graphs_6-25.srt

22.3K

10_Hubs_and_Authorities_15-16_Advanced.srt

10.2K

11_Web_Spam-_Introduction_6-50.srt

11.3K

12_Spam_Farms_8-00.srt

15.4K

13_TrustRank_10-05.srt

118 files

TEXT

BACK

14.6K

01_Distributed_File_Systems_15-50.txt

18.2K

02_The_MapReduce_Computational_Model_22-04.txt

10.7K

03_Scheduling_and_Data_Flow_12-43.txt

9.5K

04_Combiners_and_Partition_Functions_12-17_Advanced.txt

9.4K

05_Link_Analysis_and_PageRank_9-39.txt

8.5K

06_PageRank-_The_Flow_Formulation_9-16.txt

7.0K

07_PageRank-_The_Matrix_Formulation_8-02.txt

9.3K

08_PageRank-_Power_Iteration_10-34.txt

11.1K

09_PageRank-_The_Google_Formulation_12-08.txt

10.8K

10_Why_Teleports_Solve_the_Problem_12-26.txt

12.5K

11_How_we_Really_Compute_PageRank_13-49.txt

11.6K

01_Finding_Similar_Sets_13-37.txt

18.6K

02_Minhashing_25-18.txt

15.8K

03_Locality-Sensitive_Hashing_19-24.txt

10.7K

04_Applications_of_LSH_11-40.txt

6.2K

05_Fingerprint_Matching_7-07.txt

5.7K

06_Finding_Duplicate_News_Articles_6-08.txt

18.9K

07_Distance_Measures_22-39.txt

10.9K

08_Nearest_Neighbor_Learning_11-39.txt

23.3K

09_Frequent_Itemsets_29-50.txt

10.5K

10_A-Priori_Algorithm_13-07.txt

15.0K

11_Improvements_to_A-Priori_17-26__Advanced.txt

12.9K

12_All_or_Most_Frequent_Itemsets_in_2_Passes_14-40_Advanced.txt

5.9K

01_Community_Detection_in_Graphs-_Motivation_5-44.txt

10.1K

02_The_Affiliation_Graph_Model_10-04.txt

8.4K

03_From_AGM_to_BIGCLAM_8-48.txt

8.6K

04_Solving_the_BIGCLAM_9-19.txt

8.6K

05_Detecting_Communities_as_Clusters_8-39_Advanced.txt

8.2K

06_What_Makes_a_Good_Cluster_8-48_Advanced.txt

6.7K

07_The_Graph_Laplacian_Matrix_6-51_Advanced.txt

5.9K

08_Examples_of_Eigendecompositions_of_Graphs_6-16_Advanced.txt

3.1K

09_Defining_the_Graph_Laplacian_3-27_Advanced.txt

12.3K

10_Spectral_Graph_Partitioning-_Finding_a_Partition_13-25_Advanced.txt

6.9K

11_Spectral_Clustering-_Three_Steps_7-17_Advanced.txt

7.6K

12_Analysis_of_Large_Graphs-_Trawling_9-02_Advanced.txt

10.1K

13_Mining_Data_Streams_12-01.txt

20.7K

14_Counting_1s_29-00_Advanced.txt

12.7K

15_Bloom_Filters_18-00.txt

10.1K

16_Sampling_a_Stream_11-30.txt

20.3K

17_Counting_Distinct_Elements_25-59_Advanced.txt

16.2K

01_Overview_of_Recommender_Systems_16-51.txt

17.3K

02_Content-Based_Recommendations_21-00.txt

17.6K

03_Collaborative_Filtering_20-52.txt

11.7K

04_Implementing_Collaborative_Filtering_13-46_Advanced.txt

5.2K

05_Evaluating_Recommender_Systems_6-09.txt

12.2K

06_Dimensionality_Reduction-_Introduction_12-01.txt

12.9K

07_Singular-Value_Decomposition_13-39.txt

8.5K

08_Dimensionality_Reduction_with_SVD_9-04.txt

7.5K

09_SVD_Gives_the_Best_Low-Rank_Approximation_8-28_Advanced.txt

10.8K

10_SVD_Example_and_Conclusion_11-58.txt

5.7K

11_CUR_Decomposition_6-27_Advanced.txt

5.5K

12_The_CUR_Algorithm_6-15_Advanced.txt

6.6K

13_Discussion_of_the_CUR_Method_7-09.txt

14.4K

14_Latent-Factor_Models_16-11.txt

12.4K

15_Latent-Factor_Recommender_System_14-16.txt

12.2K

16_Finding_the_Latent_Factors_13-20.txt

8.2K

17_Extension_to_Include_Global_Effects_9-42_Advanced.txt

8.0K

01_Overview_of_Clustering_8-46.txt

12.0K

02_Hierarchical_Clustering_14-07.txt

11.9K

03_The_k-Means_Algorithm_12-49.txt

21.9K

04_The_BFR_Algorithm_25-01.txt

14.4K

05_The_CURE_Algorithm_15-13_Advanced.txt

20.5K

06_Computational_Advertising-_Bipartite_Graph_Matching_24-47.txt

17.0K

07_The_AdWords_Problem_19-21.txt

13.4K

08_The_Balance_Algorithm_15-16.txt

11.2K

09_Generalized_Balance_14-35_Advanced.txt

6.7K

01_Support_Vector_Machines-_Introduction_7-30.txt

10.8K

02_Support_Vector_Machines-_Mathematical_Formulation_12-15.txt

7.1K

03_What_is_the_Margin_8-22.txt

8.7K

04_Soft-Margin_SVMs_9-46.txt

13.0K

05_How_to_Compute_the_Margin_14-36_Advanced.txt

6.5K

06_Support_Vector_Machines-_Example_7-07.txt

8.0K

07_Decision_Trees_8-33.txt

12.9K

08_How_to_Construct_a_Tree_13-21.txt

8.7K

09_Information_Gain_9-50.txt

7.5K

10_Building_Decision_Trees_Using_MapReduce_8-14_Advanced.txt

6.9K

11_Decision_Trees-_Conclusion_7-25.txt

9.6K

12_MapReduce_Algorithms_Part_I_10-51_Advanced.txt

8.1K

13_MapReduce_Algorithms_Part_II_9-46_Advanced.txt

16.4K

14_Theory_of_MapReduce_Algorithms_19-39_Advanced.txt

18.8K

15_Matrix_Multiplication_in_MapReduce_24-48_Advanced.txt

16.4K

01_LSH_Families_21-13.txt

10.5K

02_More_About_LSH_Families_12-57.txt

8.7K

03_Sets_and_Strings_With_a_High_Degree_of_Similarity_11-29_Advanced.txt

5.1K

04_Prefix_of_a_String_7-43_Advanced.txt

9.7K

05_Positions_Within_Prefixes_14-04_Advanced.txt

10.8K

06_Exploiting_Length_14-39_Advanced.txt

9.5K

07_Computing_PageRank_on_Big_Graphs_10-18_Advanced.txt

9.2K

08_Topic-Specific_PageRank_10-06.txt

6.4K

09_Application_to_Measuring_Proximity_in_Graphs_6-25.txt

13.5K

10_Hubs_and_Authorities_15-16_Advanced.txt

6.5K

11_Web_Spam-_Introduction_6-50.txt

7.1K

12_Spam_Farms_8-00.txt

9.6K

13_TrustRank_10-05.txt

2.3K

links.txt

6.3K

links.txt

1.3K

links.txt

1.3K

links.txt

1.3K

links.txt

1.2K

links.txt

1.3K

links.txt

1.3K

links.txt

1.3K

links.txt

1.3K

links.txt

1.3K

links.txt

1.4K

links.txt

1.5K

links.txt

1.3K

links.txt

1.3K

links.txt

1.3K

links.txt

1.3K

links.txt

1.3K

links.txt

1.3K

links.txt

1.3K

links.txt

1.3K

links.txt

1.3K

links.txt

1.3K

links.txt

1.3K

links.txt

1 file

TORRENT

1 file

ZIP

1286 Files
7 Original

SHOW ALL

IN COLLECTIONS

Academic Torrents

The Dataset Collection

Uploaded by arkiver2 on August 12, 2018

[Coursera] Mining Massive Datasets (Stanford University) (mmds)

Movies Preview

Flag this item for

[Coursera] Mining Massive Datasets (Stanford University) (mmds)

plus-circle Add Review comment Reviews

DOWNLOAD OPTIONS

IN COLLECTIONS

SIMILAR ITEMS (based on metadata)

plus-circle Add Review

comment
Reviews