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

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