Coursera Web Intelligence and Big Data 2013 | F273519D523EA1CF23C9751FA7600A5F00A2B17A

Coursera Web Intelligence and Big Data 2013

Name	Coursera - Web Intelligence and Big Data (2013)	DOWNLOAD Copy Link
Total Size	1.3 GB
Total Files	213
Hash	F273519D523EA1CF23C9751FA7600A5F00A2B17A

/soft/
orange-win-w-python-snapshot-hg-2013-05-30-py2.7.exe	108.1 MB
/video/
11 - 2 - G2 Graph Query Languages (1403).mp4	22.1 MB
11 - 3 - G3 Linked Open Data (1225).mp4	21.2 MB
7 - 3 - 6-3 Resolution and its Limits (1558).mp4	21.2 MB
9 - 11 - 7-11 Homework Assignment Genomic Data Analysis.mp4	20.7 MB
6 - 7 - 5-7 Learning Latent Models (1557).mp4	20.6 MB
4 - 6 - 3-5 Map-Reduce Applications (1352).mp4	18.7 MB
11 - 1 - G1 Introduction to Graph Data (1136).mp4	18.1 MB
6 - 2 - 5-2 Classification Re-visited (1256).mp4	17.9 MB
8 - 4 - M4 Markov Logic Formalism (1139).mp4	17.5 MB
7 - 10 - 6-9 Information Extraction (1241).mp4	17.4 MB
5 - 6 - 4-5 NoSQL and Eventual Consistency (1241).mp4	17.1 MB
9 - 5 - 7-5 Learning Parameters (1235).mp4	16.9 MB
5 - 3 - 4-2 Database Technology (1240).mp4	16.9 MB
6 - 3 - 5-3 Learning Groupings - Clustering (1213).mp4	16.9 MB
11 - 5 - G5 Graph Data Management (1026).mp4	16.6 MB
4 - 4 - 3-4 Map-Reduce Example in Octo (1103).mp4	16.5 MB
8 - 5 - M5 Related Models (1021).mp4	16.2 MB
9 - 3 - 7-3 Least Squares (1208).mp4	16.1 MB
7 - 6 - 6-6 Algebra of Potentials (1205).mp4	16.1 MB
8 - 1 - M1 Motivation (1159).mp4	16.1 MB
8 - 7 - M7 Entity Resolution Example - 2 (953).mp4	15.9 MB
4 - 3 - 3-3 Map-Reduce (1149).mp4	15.6 MB
5 - 2 - 4-1 Distributed File Systems (1212).mp4	15.4 MB
7 - 7 - 6-7 Naive Bayes Revisited (1126).mp4	15.1 MB
5 - 9 - 4-8 Relational vs Big-Data Technologies (911).mp4	15.1 MB
9 - 9 - 7-9 Hierarchical Temporal Memory - II (1038).mp4	14.4 MB
11 - 4 - G4 Challenges and Efficiency (856).mp4	14.4 MB
3 - 12 - 2-11 Machine Learning - Limits (1029).mp4	14.3 MB
9 - 2 - 7-2 Linear Prediction (1100).mp4	14.3 MB
6 - 4 - 5-4 Learning Rules (1011).mp4	13.8 MB
8 - 6 - M6 Entity Resolution Example - 1 (837).mp4	13.7 MB
7 - 2 - 6-2 Logical Inference (956).mp4	13.3 MB
5 - 5 - 4-4 Big-Table and HBase (1008).mp4	12.7 MB
9 - 10 - 7-10 Blackboard Architecture (906).mp4	12.7 MB
4 - 8 - 3-7 Inside Map-Reduce (947).mp4	12.6 MB
3 - 11 - 2-10 Mutual Information (858).mp4	12.6 MB
8 - 2 - M2 Markov Networks and Logic (844).mp4	12.6 MB
5 - 10 - 4-9 Database Trends and Summary (722).mp4	12.5 MB
5 - 8 - 4-7 Evolution of SQL and Map-Reduce (934).mp4	12.4 MB
7 - 8 - 6-8-1 Bayesian Networks - 1 (920).mp4	12.4 MB
8 - 3 - M3 Markov Logic via an Example (828).mp4	12.3 MB
5 - 7 - 4-6 Future of NoSQL and Dremel (928).mp4	12.3 MB
3 - 7 - 2-7 Machine Learning Intro (900).mp4	12.3 MB
3 - 6 - 2-6 Language and Information (856).mp4	12.2 MB
7 - 1 - 6-1 Preamble (907).mp4	12.2 MB
7 - 5 - 6-5 Logic and Uncertainty (909).mp4	12.1 MB
9 - 4 - 7-4 Nonlinear Models (926) .mp4	12.1 MB
10 - 1 - Course Recap and Pointers (934).mp4	12.1 MB
6 - 5 - 5-5 Association Rule Mining (845).mp4	11.8 MB
9 - 8 - 7-8 Hierarchical Temporal Memory - I (839).mp4	11.7 MB
4 - 7 - 3-6 Parallel Efficiency of Map-Reduce (842).mp4	11.6 MB
5 - 4 - 4-3 Evolution of Databases (852).mp4	11.6 MB
9 - 6 - 7-6 Prediction Applications (830).mp4	11.5 MB
3 - 4 - 2-4 TF-IDF (824).mp4	11.4 MB
3 - 9 - 2-8-2 Naive Bayes (833).mp4	11.3 MB
4 - 2 - 3-2 Parallel Computing (854).mp4	11.2 MB
2 - 15 - 1-7-6 High-dimensional Objects (819).mp4	10.9 MB
6 - 6 - 5-6 Learning with Big Data (751).mp4	10.9 MB
8 - 8 - M8 Social Network Analysis using MLN (727).mp4	10.7 MB
3 - 10 - 2-9 Sentiment Analysis (732).mp4	10.6 MB
2 - 1 - 1-1 Basic Indexing (722).mp4	9.5 MB
7 - 11 - 6-10 Recap and Preview (700).mp4	9.5 MB
2 - 9 - 1-6-2 Searching Structured Data (625).mp4	9.0 MB
7 - 4 - 6-4 Semantic Web (618).mp4	8.7 MB
3 - 2 - 2-2 Shannon Information (618).mp4	8.6 MB
3 - 5 - 2-5 TF-IDF Example (609).mp4	8.4 MB
8 - 9 - M9 Research Directions in Markov Logic (609).mp4	8.4 MB
9 - 7 - 7-7 Which Technique (613).mp4	8.4 MB
2 - 6 - 1-5-1 Page Rank and Memory (601).mp4	8.4 MB
11 - 6 - G6 Q A (503).mp4	8.3 MB
1 - 5 - 0-3-2 Big Data (615).mp4	8.3 MB
2 - 16 - 1-7-7 Associative Memories (525).mp4	8.1 MB
3 - 3 - 2-3 Information and Advertising (549).mp4	7.8 MB
6 - 8 - 5-8 Grounded Learning (542).mp4	7.7 MB
7 - 9 - 6-8-2 Bayesian Networks - 2 (523).mp4	7.6 MB
2 - 2 - 1-2 Index Creation (540).mp4	7.5 MB
2 - 7 - 1-5-2 Google and the Mind (518).mp4	7.5 MB
1 - 7 - 0-5 Recap and Preview (237).mp4	7.0 MB
2 - 10 - 1-7-1 Object Search (507).mp4	6.9 MB
2 - 5 - 1-4-2 Ranking - 2 (448).mp4	6.7 MB
3 - 8 - 2-8-1 Bayes Rule (455).mp4	6.5 MB
2 - 11 - 1-7-2 Locality Sensitive Hashing (451).mp4	6.5 MB
1 - 6 - 0-4 Course Outline (413).mp4	6.4 MB
1 - 1 - 0-0 Preamble (326).mp4	6.3 MB
2 - 8 - 1-6-1 Enterprise Search (441).mp4	6.3 MB
7 - 12 - 6-11-Programming HW 6 (424).mp4	6.2 MB
4 - 1 - 3-1 Preamble (441).mp4	6.1 MB
2 - 4 - 1-4-1 Ranking - 1 (424).mp4	5.6 MB
1 - 3 - 0-2 Web-Scale AI and Big Data (358).mp4	5.5 MB
2 - 14 - 1-7-5 LSH Intuition (408).mp4	5.3 MB
2 - 12 - 1-7-3 LSH Example - 1 (317).mp4	5.0 MB
2 - 3 - 1-3 Complexity of Index Creation (328).mp4	5.0 MB
1 - 4 - 0-3-1 Web Intelligence (322).mp4	4.8 MB
3 - 13 - 2-12 Recap and Preview (314).mp4	4.5 MB
1 - 2 - 0-1 Revisiting Turings Test (309).mp4	4.4 MB
6 - 1 - 5-1 Preamble (318).mp4	4.2 MB
3 - 1 - 2-1 Preamble - Listen (318).mp4	4.1 MB
6 - 9 - 5-9 Recap and Preview (233).mp4	3.4 MB
9 - 1 - 7-1 Preamble (234).mp4	3.2 MB
2 - 17 - 1-7-8 Recap and Preview (244).mp4	3.1 MB
2 - 13 - 1-7-4 LSH Example - 2 (154).mp4	3.0 MB
4 - 5 - 3-4-1 Map-Reduce Example in Mincemeat (204).mp4	2.9 MB
5 - 1 - 4-0 Preamble (143).mp4	2.1 MB
/assignments/
hw7_genestrain.tab.zip	6.5 MB
hw3_data.zip	2.7 MB
hw7_genesblind.tab.zip	1.2 MB
hw6_assignment2.pdf	188.9 KB
hw7_assignment3.pdf	131.6 KB
hw3_assignment1.pdf	97.0 KB
/slides/
7-Predict-Lecture-Slides.pdf	4.0 MB
3-Load Lecture Slides.pdf	1.8 MB
2-Listen Lecture Slides.pdf	1.6 MB
4-Load Lecture Slides.pdf	1.5 MB
1-Look Lecture Slides.pdf	1.2 MB
0-Introduction Lecture Slides.pdf	862.4 KB
5-Learn Lecture Slides.pdf	554.6 KB
6-Connect-Revised-Slides.pdf	333.0 KB
/
references_resources.pdf	94.4 KB
course schedule spring 2013 v2.pdf	91.3 KB
/subtitles/
11 - 2 - G2 Graph Query Languages (1403).srt	18.3 KB
6 - 7 - 5-7 Learning Latent Models (1557).srt	16.7 KB
7 - 3 - 6-3 Resolution and its Limits (1558).srt	16.1 KB
11 - 3 - G3 Linked Open Data (1225).srt	15.7 KB
11 - 1 - G1 Introduction to Graph Data (1136).srt	15.2 KB
9 - 5 - 7-5 Learning Parameters (1235).srt	15.1 KB
4 - 6 - 3-5 Map-Reduce Applications (1352).srt	14.6 KB
9 - 3 - 7-3 Least Squares (1208).srt	14.4 KB
7 - 10 - 6-9 Information Extraction (1241).srt	14.1 KB
6 - 3 - 5-3 Learning Groupings - Clustering (1213).srt	14.0 KB
6 - 2 - 5-2 Classification Re-visited (1256).srt	13.9 KB
5 - 2 - 4-1 Distributed File Systems (1212).srt	13.4 KB
5 - 3 - 4-2 Database Technology (1240).srt	13.3 KB
7 - 7 - 6-7 Naive Bayes Revisited (1126).srt	13.1 KB
11 - 5 - G5 Graph Data Management (1026).srt	12.9 KB
5 - 6 - 4-5 NoSQL and Eventual Consistency (1241).srt	12.6 KB
9 - 9 - 7-9 Hierarchical Temporal Memory - II (1038).srt	12.5 KB
9 - 2 - 7-2 Linear Prediction (1100).srt	12.3 KB
4 - 3 - 3-3 Map-Reduce (1149).srt	12.2 KB
7 - 6 - 6-6 Algebra of Potentials (1205).srt	12.0 KB
10 - 1 - Course Recap and Pointers (934).srt	11.9 KB
4 - 4 - 3-4 Map-Reduce Example in Octo (1103).srt	11.8 KB
5 - 9 - 4-8 Relational vs Big-Data Technologies (911).srt	11.6 KB
11 - 4 - G4 Challenges and Efficiency (856).srt	11.4 KB
7 - 8 - 6-8-1 Bayesian Networks - 1 (920).srt	11.2 KB
5 - 5 - 4-4 Big-Table and HBase (1008).srt	11.0 KB
9 - 10 - 7-10 Blackboard Architecture (906).srt	11.0 KB
5 - 8 - 4-7 Evolution of SQL and Map-Reduce (934).srt	10.9 KB
3 - 12 - 2-11 Machine Learning - Limits (1029).srt	10.8 KB
6 - 4 - 5-4 Learning Rules (1011).srt	10.6 KB
5 - 7 - 4-6 Future of NoSQL and Dremel (928).srt	10.6 KB
9 - 6 - 7-6 Prediction Applications (830).srt	10.5 KB
7 - 1 - 6-1 Preamble (907).srt	10.4 KB
9 - 4 - 7-4 Nonlinear Models (926) .srt	10.4 KB
4 - 8 - 3-7 Inside Map-Reduce (947).srt	10.4 KB
9 - 8 - 7-8 Hierarchical Temporal Memory - I (839).srt	10.3 KB
4 - 2 - 3-2 Parallel Computing (854).srt	9.7 KB
5 - 10 - 4-9 Database Trends and Summary (722).srt	9.7 KB
3 - 11 - 2-10 Mutual Information (858).srt	9.5 KB
5 - 4 - 4-3 Evolution of Databases (852).srt	9.4 KB
7 - 2 - 6-2 Logical Inference (956).srt	9.3 KB
6 - 5 - 5-5 Association Rule Mining (845).srt	9.1 KB
3 - 7 - 2-7 Machine Learning Intro (900).srt	8.9 KB
3 - 4 - 2-4 TF-IDF (824).srt	8.8 KB
6 - 6 - 5-6 Learning with Big Data (751).srt	8.8 KB
3 - 6 - 2-6 Language and Information (856).srt	8.8 KB
7 - 5 - 6-5 Logic and Uncertainty (909).srt	8.5 KB
3 - 9 - 2-8-2 Naive Bayes (833).srt	8.5 KB
9 - 7 - 7-7 Which Technique (613).srt	8.2 KB
3 - 10 - 2-9 Sentiment Analysis (732).srt	8.2 KB
7 - 11 - 6-10 Recap and Preview (700).srt	7.8 KB
2 - 15 - 1-7-6 High-dimensional Objects (819).srt	7.8 KB
2 - 1 - 1-1 Basic Indexing (722).srt	7.4 KB
11 - 6 - G6 Q A (503).srt	6.8 KB
3 - 5 - 2-5 TF-IDF Example (609).srt	6.7 KB
7 - 4 - 6-4 Semantic Web (618).srt	6.5 KB
2 - 9 - 1-6-2 Searching Structured Data (625).srt	6.4 KB
7 - 9 - 6-8-2 Bayesian Networks - 2 (523).srt	6.3 KB
6 - 8 - 5-8 Grounded Learning (542).srt	6.2 KB
2 - 2 - 1-2 Index Creation (540).srt	6.0 KB
4 - 7 - 3-6 Parallel Efficiency of Map-Reduce (842).srt	6.0 KB
2 - 6 - 1-5-1 Page Rank and Memory (601).srt	5.8 KB
3 - 2 - 2-2 Shannon Information (618).srt	5.7 KB
3 - 3 - 2-3 Information and Advertising (549).srt	5.5 KB
1 - 6 - 0-4 Course Outline (413).srt	5.4 KB
1 - 5 - 0-3-2 Big Data (615).srt	5.4 KB
4 - 1 - 3-1 Preamble (441).srt	5.4 KB
2 - 10 - 1-7-1 Object Search (507).srt	5.3 KB
2 - 5 - 1-4-2 Ranking - 2 (448).srt	5.0 KB
2 - 8 - 1-6-1 Enterprise Search (441).srt	5.0 KB
7 - 12 - 6-11-Programming HW 6 (424).srt	4.9 KB
2 - 7 - 1-5-2 Google and the Mind (518).srt	4.9 KB
3 - 8 - 2-8-1 Bayes Rule (455).srt	4.8 KB
2 - 11 - 1-7-2 Locality Sensitive Hashing (451).srt	4.5 KB
2 - 4 - 1-4-1 Ranking - 1 (424).srt	4.4 KB
1 - 1 - 0-0 Preamble (326).srt	4.4 KB
1 - 3 - 0-2 Web-Scale AI and Big Data (358).srt	4.2 KB
2 - 14 - 1-7-5 LSH Intuition (408).srt	3.9 KB
2 - 3 - 1-3 Complexity of Index Creation (328).srt	3.7 KB
3 - 13 - 2-12 Recap and Preview (314).srt	3.6 KB
1 - 2 - 0-1 Revisiting Turings Test (309).srt	3.4 KB
1 - 7 - 0-5 Recap and Preview (237).srt	3.2 KB
6 - 1 - 5-1 Preamble (318).srt	3.2 KB
1 - 4 - 0-3-1 Web Intelligence (322).srt	3.1 KB
9 - 1 - 7-1 Preamble (234).srt	3.0 KB
3 - 1 - 2-1 Preamble - Listen (318).srt	2.9 KB
2 - 17 - 1-7-8 Recap and Preview (244).srt	2.8 KB
4 - 5 - 3-4-1 Map-Reduce Example in Mincemeat (204).srt	2.7 KB
6 - 9 - 5-9 Recap and Preview (233).srt	2.6 KB
2 - 12 - 1-7-3 LSH Example - 1 (317).srt	2.6 KB
5 - 1 - 4-0 Preamble (143).srt	1.9 KB
2 - 13 - 1-7-4 LSH Example - 2 (154).srt	1.9 KB
2 - 16 - 1-7-7 Associative Memories (525).srt	1.1 KB
Total files 213