mining

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2 - 1 - Distributed File Systems (15_50).srt

2 - 1 - Distributed File Systems (15_50).srt

2 - 2 - The MapReduce Computational Model (22_04).srt

2 - 2 - The MapReduce Computational Model (22_04).srt

2 - 3 - Scheduling and Data Flow (12_43).srt

2 - 3 - Scheduling and Data Flow (12_43).srt

2 - 4 - Combiners and Partition Functions (12_17) [Advanced].srt

2 - 4 - Combiners and Partition Functions (12_17) [Advanced].srt

2 - 5 - Link Analysis and PageRank (9_39).srt

2 - 5 - Link Analysis and PageRank (9_39).srt

2 - 6 - PageRank_ The Flow Formulation (9_16).srt

2 - 6 - PageRank_ The Flow Formulation (9_16).srt

2 - 7 - PageRank_ The Matrix Formulation (8_02).srt

2 - 7 - PageRank_ The Matrix Formulation (8_02).srt

2 - 8 - PageRank_ Power Iteration (10_34).srt

2 - 8 - PageRank_ Power Iteration (10_34).srt

2 - 9 - PageRank_ The Google Formulation (12_08).srt

2 - 9 - PageRank_ The Google Formulation (12_08).srt

2 - 10 - Why Teleports Solve the Problem (12_26).srt

2 - 10 - Why Teleports Solve the Problem (12_26).srt

2 - 11 - How we Really Compute PageRank (13_49).srt

2 - 11 - How we Really Compute PageRank (13_49).srt

3 - 1 - Finding Similar Sets (13_37).srt

3 - 1 - Finding Similar Sets (13_37).srt

3 - 2 - Minhashing (25_18).srt

3 - 2 - Minhashing (25_18).srt

3 - 3 - Locality-Sensitive Hashing (19_24).srt

3 - 3 - Locality-Sensitive Hashing (19_24).srt

3 - 4 - Applications of LSH (11_40).srt

3 - 4 - Applications of LSH (11_40).srt

3 - 5 - Fingerprint Matching (7_07).srt

3 - 5 - Fingerprint Matching (7_07).srt

3 - 6 - Finding Duplicate News Articles (6_08).srt

3 - 6 - Finding Duplicate News Articles (6_08).srt

3 - 7 - Distance Measures (22_39).srt

3 - 7 - Distance Measures (22_39).srt

3 - 8 - Nearest Neighbor Learning (11_39).srt

3 - 8 - Nearest Neighbor Learning (11_39).srt

3 - 9 - Frequent Itemsets (29_50).srt

3 - 9 - Frequent Itemsets (29_50).srt

3 - 10 - A-Priori Algorithm (13_07).srt

3 - 10 - A-Priori Algorithm (13_07).srt

3 - 11 - Improvements to A-Priori (17_26) [Advanced].srt

3 - 11 - Improvements to A-Priori (17_26) [Advanced].srt

3 - 12 - All or Most Frequent Itemsets in 2 Passes (14_40) [Advanced].srt

3 - 12 - All or Most Frequent Itemsets in 2 Passes (14_40) [Advanced].srt

4 - 1 - Community Detection in Graphs_ Motivation (5_44).srt

4 - 1 - Community Detection in Graphs_ Motivation (5_44).srt

4 - 2 - The Affiliation Graph Model (10_04).srt

4 - 2 - The Affiliation Graph Model (10_04).srt

4 - 3 - From AGM to BIGCLAM (8_48).srt

4 - 3 - From AGM to BIGCLAM (8_48).srt

4 - 4 - Solving the BIGCLAM (9_19).srt

4 - 4 - Solving the BIGCLAM (9_19).srt

4 - 5 - Detecting Communities as Clusters (8_39) [Advanced].srt

4 - 5 - Detecting Communities as Clusters (8_39) [Advanced].srt

4 - 6 - What Makes a Good Cluster_ (8_48) [Advanced].srt

4 - 6 - What Makes a Good Cluster_ (8_48) [Advanced].srt

4 - 7 - The Graph Laplacian Matrix (6_51) [Advanced].srt

4 - 7 - The Graph Laplacian Matrix (6_51) [Advanced].srt

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