TorBT - Torrents and Magnet Links Search Engine
Latest Searches: pedomummy, three+hopes, slipknot discography, meguil, amg, sing+sing, battle+league, granny%2f, prince - prince, bleeding+steel

Coursera - Introduction to Data Science (2013)

Magnet Download Download Torrent
File Name
Size
virtual machine/Coursera-Data-Science-Ubuntu.ova
2.3 GB
soft/TableauDesktop.exe
87 MB
video-extra/Introduction to JSMapreduce.mp4
49 MB
video/8 - 2 - Eventual Consistency (1856).mp4
26 MB
video/1 - 11 - Twitter Assignment Getting Started with Problem 0 and Problem 1.mp4
25 MB
video/1 - 1 - Appetite Whetting Part 1 (1538).mp4
24 MB
video/8 - 7 - Example Other Google Systems (1618).mp4
24 MB
video/8 - 3 - Example Memcached (1637).mp4
23 MB
video/3 - 1 - Scalability Basics (1618).mp4
23 MB
video/3 - 9 - Parallel Databases (1618).mp4
23 MB
video/8 - 11 - Pig Join and Co-Group Join (1610).mp4
22 MB
video/1 - 8 - Big Data (1436).mp4
22 MB
video/10 - 1 - 01 Guest Segment Aaron Kimball Wibidata.mp4
21 MB
video/1 - 2 - Appetite Whetting Part 2 (1344).mp4
20 MB
video/3 - 11 - Experimental Results MR and DB (1501).mp4
20 MB
video/1 - 5 - This Course Part 1 (1402).mp4
20 MB
video/8 - 8 - Response to NoSQL Systems (1444).mp4
19 MB
video/5 - 6 - 06 Information Gain (1143).mp4
19 MB
video/3 - 6 - MapReduce Relational Join Social Example (1317).mp4
19 MB
video/2 - 7 - SQL for Data Science Interpreting Complicated SQL (1212).mp4
18 MB
video/3 - 8 - MapReduce Implementation Overview (1338).mp4
18 MB
video/4 - 8 - Bayes Rule (1153).mp4
18 MB
video/4 - 6 - Recap and Big Data (1139).mp4
18 MB
video/1 - 9 - Guest Lecture Biomedical Informatics (1024).mp4
17 MB
video/4 - 1 - Statistics Intro (1036).mp4
17 MB
video/3 - 3 - MapReduce Abstractions (1117).mp4
17 MB
video/5 - 12 - 12 k Nearest Neighbors (1143).mp4
17 MB
video/5 - 11 - 11 Random Forests (1116).mp4
17 MB
video/1 - 7 - eScience (1146).mp4
17 MB
video/4 - 5 - Multiple Hypothesis Testing (1122).mp4
16 MB
video/8 - 10 - Pig Functions (1141).mp4
16 MB
video/3 - 2 - Parallel Processing Patterns (1126).mp4
16 MB
video/5 - 7 - 07 Overfitting (1104).mp4
16 MB
video/7 - 8 - 08 PRISM Example in Datalog (1110).mp4
16 MB
video/3 - 5 - MapReduce Text Examples (958).mp4
16 MB
video/2 - 5 - Relational Algebra Details Project Cross Product Equi-Join (1106).mp4
16 MB
video/2 - 9 - Physical Optimization (1114).mp4
16 MB
video/4 - 4 - Fraud and Benfords Law (1055).mp4
16 MB
video/2 - 4 - Relational Algebra Details Union Diff Select (1053).mp4
16 MB
video/2 - 3 - Relational Algebra Introduction (1058).mp4
16 MB
video/5 - 5 - 05 Decision Trees Entropy (1051).mp4
16 MB
video/9 - 3 - 03 Intuition for Logistic Regression and Support Vector Machines (1055).mp4
16 MB
video/8 - 6 - Example BigTable (1105).mp4
16 MB
video/5 - 8 - 08 Evaluation and Cross-Validation (1046).mp4
15 MB
video/8 - 9 - Pig Intro (1202).mp4
15 MB
video/2 - 10 - Declarative Languages (1030).mp4
15 MB
video/7 - 12 - 12 PageRank in MapReduce and Pregel (1042).mp4
15 MB
video/2 - 1 - From Data Models to Databases (1035).mp4
15 MB
video/8 - 12 - Pig Evaluation (1011).mp4
14 MB
video/4 - 3 - Effect Size Meta-analysis Heteroskedasticity (931).mp4
14 MB
video/1 - 6 - This Course Part 2 (1050).mp4
14 MB
video/8 - 5 - Example CouchDB (1000).mp4
14 MB
video/2 - 11 - Logical Data Independence (1123).mp4
14 MB
video/7 - 6 - 06 Patterns Triangles SPARQL Datalog (1002).mp4
14 MB
video/5 - 10 - 10 Ensembles Bagging and Boosting (0919).mp4
14 MB
video/8 - 4 - Example Dynamo (1016).mp4
14 MB
video/9 - 8 - 08 DBSCAN (0913).mp4
14 MB
video/6 - 2 - 02 Data Types (937).mp4
14 MB
video/1 - 3 - Context (930).mp4
13 MB
video/3 - 7 - MapReduce Matrix Multiply Example (931).mp4
13 MB
video/9 - 5 - 05 Stochastic Gradient Descent Minibatches Parallelization (0853).mp4
13 MB
video/4 - 2 - Publication Bias (845).mp4
13 MB
video/10 - 2 - 02 Guest Segment Karen Hsu Datameer.mp4
13 MB
video/5 - 3 - 03 Rules Part 1 (0919).mp4
13 MB
video/8 - 1 - NoSQL Introduction (830).mp4
13 MB
video/1 - 4 - Dimensions (1024).mp4
13 MB
video/2 - 2 - Motivating Relational Algebra (857).mp4
13 MB
video/4 - 7 - Bayesian Intro (759).mp4
12 MB
video/3 - 4 - MapReduce Pseudocode (754).mp4
12 MB
video/2 - 6 - Relational Algebra Details Theta-Join (834).mp4
12 MB
video/7 - 10 - 10 Optimizing MapReduce for Graph Traversal (0820).mp4
12 MB
video/7 - 7 - 07 Patterns Relational Algebra for Graph Query (0826).mp4
12 MB
video/7 - 2 - 02 Structure Degree Histograms (0814).mp4
12 MB
video/5 - 1 - 01 Introduction to Machine Learning Part 1 (0754).mp4
12 MB
video/7 - 9 - 09 Evaluating Graph Traversal Queries (0829).mp4
12 MB
video/2 - 8 - SQL for Data Science User-Defined Functions (759).mp4
11 MB
video/1 - 10 - Logistics (742).mp4
11 MB
video/7 - 5 - 05 Traversal Spanning Trees Circuits Flows (0657).mp4
10 MB
video/6 - 1 - 01 Introduction (717).mp4
10 MB
video/9 - 1 - 01 Gradient Descent Part 1 (0718).mp4
10 MB
video/9 - 4 - 04 Intuition for Regularization (0659).mp4
9.9 MB
video/7 - 11 - 11 Graph Representations (0651).mp4
9.7 MB
video/7 - 3 - 03 Structure Diameter Connectivity Centrality (0656).mp4
9.6 MB
video/6 - 5 - 05 Visual Encoding (Part 1) (638).mp4
9.6 MB
video/7 - 4 - 04 Traversal PageRank (0637).mp4
9.4 MB
video/9 - 2 - 02 Gradient Descent Part 2 (0629).mp4
9.1 MB
video/3 - 10 - Comparing MapReduce and Databases (0639).mp4
9.0 MB
video/7 - 1 - 01 Graph Basics (0622).mp4
8.7 MB
video/9 - 6 - 06 Unsupervised Learning (0611).mp4
8.7 MB
video/5 - 4 - 04 Rules Part 2 (0539).mp4
8.6 MB
video/5 - 2 - 02 Introduction to Machine Learning Part 2 (0523).mp4
8.0 MB
video/9 - 7 - 07 K-means (0556).mp4
8.0 MB
video/5 - 9 - 09 The Bootstrap (0413).mp4
6.6 MB
video/6 - 7 - 07 Visual Perception (Part 1) (439).mp4
6.5 MB
assignments/6_VisualizationAssignment.twbx
6.0 MB
video/6 - 8 - 08 Visual Perception (Part 2) (418).mp4
6.0 MB
video/6 - 3 - 03 Data Types (Exercises) (407).mp4
5.9 MB
video/6 - 9 - 09 Visual Perception (Part 3) (356).mp4
5.3 MB
video/6 - 10 - 10 Evaluation (325).mp4
5.0 MB
video/6 - 4 - 04 Data Dimensions (308).mp4
4.4 MB
video/6 - 6 - 06 Visual Encoding (Part 2) (254).mp4
4.2 MB
slides/016_parallel_thinking.pdf
3.1 MB
slides/005_escience.pdf
2.6 MB
slides/017_map_reduce_abstraction.pdf
2.2 MB
slides/059_gradient_descent_part_1.pdf
1.4 MB
slides/006_big_data.pdf
1.3 MB
slides/041_fraud_benfords_law.pdf
1.2 MB
slides/000b_appetite_whetting_2.pdf
1.1 MB
slides/000_appetite_whetting_1.pdf
1.0 MB
slides/Infovis Aragon 2 Data Types.pdf
955 kB
slides/Infovis Aragon 7 Visual Perception (Part 1).pdf
885 kB
docs/Running Tableau on AWS.pdf
874 kB
slides/087_pagerank_mapreduce_pregel.pdf
804 kB
slides/Infovis Aragon 5 Visual Encoding (Part 1).pdf
750 kB
slides/033_nosql_response.pdf
747 kB
slides/guests-kiji-uw-data-science.pdf
736 kB
slides/025_mapreduce_and_databases_experiments.pdf
730 kB
slides/032_other_google_systems.pdf
729 kB
slides/027_eventual_consistency.pdf
718 kB
slides/003_this_course_1.pdf
704 kB
slides/Infovis Aragon 6 Visual Encoding (Part 2).pdf
685 kB
slides/Infovis Aragon 1 Introduction.pdf
674 kB
slides/Infovis Aragon 4 Data Dimensions.pdf
671 kB
slides/013_declarative_languages.pdf
661 kB
slides/043_recap_and_big_data.pdf
659 kB
slides/061_intuition_logistic_regression_svms.pdf
640 kB
slides/066_dbscan.pdf
636 kB
slides/008_data_models.pdf
620 kB
slides/060_gradient_descent_part_2.pdf
595 kB
slides/028_memcached.pdf
586 kB
slides/011.8_interpreting_complicated_sql.pdf
577 kB
slides/084_evaluating_recursive_programs.pdf
577 kB
slides/040_effect_size_meta_analysis_heteroskedasticity.pdf
568 kB
slides/030_couchdb.pdf
562 kB
slides/064_unsupervised_learning_copy.pdf
551 kB
slides/034_pig_intro.pdf
527 kB
slides/026_nosql_intro.pdf
525 kB
slides/022_map_reduce_implementation_overview.pdf
501 kB
slides/011.7_theta_join.pdf
492 kB
slides/063_stochastic_gradient_descent.pdf
490 kB
slides/062_intuition_regularization.pdf
490 kB
slides/049_rules_1.pdf
484 kB
slides/031_bigtable.pdf
483 kB
slides/077b_graph_histograms.pdf
482 kB
slides/051_intro_trees.pdf
477 kB
slides/014_logical_data_independence.pdf
469 kB
slides/081_pattern_matching.pdf
468 kB
slides/042_multiple_hypothesis_testing_CORRECTED.pdf
468 kB
slides/029_dynamo.pdf
466 kB
slides/Infovis Aragon 8 Visual Perception (Part 2).pdf
450 kB
slides/085_optimizing_recursive_programs_in_mr.pdf
438 kB
slides/001_context.pdf
430 kB
slides/012_physical_optimization.pdf
427 kB
slides/Infovis Aragon 3 Data Types (Exercises).pdf
424 kB
slides/086_graph_representations.pdf
424 kB
slides/052_information_gain.pdf
419 kB
slides/045_bayes_rule.pdf
409 kB
slides/039_publication_bias.pdf
408 kB
slides/080_traversal_tasks.pdf
400 kB
slides/078_structural_analysis_tasks.pdf
399 kB
slides/023_parallel_databases.pdf
386 kB
slides/004_this_course_2.pdf
383 kB
slides/011.6_relational_algebra_project_cross_equijoin.pdf
381 kB
slides/011.5_relational_algebra_union_diff_select.pdf
364 kB
slides/053_overfitting.pdf
347 kB
slides/007_logistics.pdf
345 kB
slides/019_map_reduce_text_examples.pdf
338 kB
slides/037_pig_evaluation.pdf
336 kB
slides/Infovis Aragon 9 Visual Perception (Part 3).pdf
330 kB
slides/047_overview_machine_learning.pdf
328 kB
slides/020_map_reduce_join_social_examples.pdf
326 kB
slides/021_map_reduce_matrix_multiply.pdf
318 kB
slides/Infovis Aragon 10 Evaluation.pdf
298 kB
slides/009_relational_motivation.pdf
294 kB
slides/055_bootstrap.pdf
285 kB
slides/002_dimensions.pdf
282 kB
slides/079_pagerank.pdf
279 kB
slides/050_rules_2.pdf
278 kB
slides/054_evaluation_thresholds.pdf
271 kB
assignments/4_aws-setup.pdf
270 kB
assignments/1_instructions.pdf
261 kB
assignments/4_quiz.pdf
258 kB
assignments/3_js_quiz.pdf
255 kB
slides/056_ensembles_and_boosting.pdf
242 kB
slides/036_cogroup_join.pdf
234 kB
slides/015_scalability.pdf
224 kB
docs/Syllabus.pdf
203 kB
assignments/2_instructions.pdf
195 kB
slides/035_pig_load_filter_group_foreach.pdf
191 kB
slides/guests-datameer_beyond_mapreduce.pdf
189 kB
slides/058_nearest_neighbor.pdf
188 kB
slides/065_kmeans.pdf
181 kB
slides/010_relational_algebra_intro.pdf
157 kB
slides/038_stats_intro.pdf
149 kB
slides/083_prism_example.pdf
147 kB
assignments/3_python_instructions.pdf
142 kB
docs/Github Instructions.pdf
128 kB
docs/Course Logistics.pdf
124 kB
slides/044_intro_bayesian.pdf
104 kB
slides/024_mapreduce_and_databases.pdf
95 kB
slides/018_map_reduce_pseudocode.pdf
94 kB
slides/048_intro_machine_learning_2.pdf
93 kB
slides/082_relational_algebra_for_graph_tasks.pdf
91 kB
docs/Class Virtual Machine.pdf
89 kB
slides/057_random_forests.pdf
88 kB
docs/Python Resources.pdf
84 kB
slides/011.9_user_defined_functions.pdf
62 kB
subtitles/8 - 2 - Eventual Consistency (1856).srt
29 kB
subtitles/1 - 8 - Big Data (1436).srt
25 kB
subtitles/8 - 7 - Example Other Google Systems (1618).srt
25 kB
subtitles/3 - 9 - Parallel Databases (1618).srt
24 kB
subtitles/3 - 1 - Scalability Basics (1618).srt
24 kB
subtitles/8 - 3 - Example Memcached (1637).srt
23 kB
subtitles/8 - 11 - Pig Join and Co-Group Join (1610).srt
23 kB
subtitles/1 - 5 - This Course Part 1 (1402).srt
22 kB
subtitles/1 - 1 - Appetite Whetting Part 1 (1538).srt
22 kB
subtitles/8 - 8 - Response to NoSQL Systems (1444).srt
22 kB
subtitles/3 - 11 - Experimental Results MR and DB (1501).srt
20 kB
subtitles/3 - 8 - MapReduce Implementation Overview (1338).srt
20 kB
subtitles/1 - 7 - eScience (1146).srt
19 kB
subtitles/2 - 7 - SQL for Data Science Interpreting Complicated SQL (1212).srt
19 kB
subtitles/1 - 2 - Appetite Whetting Part 2 (1344).srt
18 kB
subtitles/8 - 9 - Pig Intro (1202).srt
18 kB
subtitles/2 - 1 - From Data Models to Databases (1035).srt
18 kB
subtitles/3 - 6 - MapReduce Relational Join Social Example (1317).srt
18 kB
subtitles/5 - 6 - 06 Information Gain (1143).srt
17 kB
subtitles/3 - 3 - MapReduce Abstractions (1117).srt
17 kB
subtitles/2 - 3 - Relational Algebra Introduction (1058).srt
17 kB
subtitles/5 - 7 - 07 Overfitting (1104).srt
17 kB
subtitles/4 - 6 - Recap and Big Data (1139).srt
17 kB
subtitles/2 - 9 - Physical Optimization (1114).srt
16 kB
subtitles/1 - 4 - Dimensions (1024).srt
16 kB
subtitles/1 - 6 - This Course Part 2 (1050).srt
16 kB
subtitles/3 - 2 - Parallel Processing Patterns (1126).srt
16 kB
subtitles/5 - 11 - 11 Random Forests (1116).srt
16 kB
subtitles/8 - 10 - Pig Functions (1141).srt
16 kB
subtitles/5 - 12 - 12 k Nearest Neighbors (1143).srt
16 kB
subtitles/1 - 3 - Context (930).srt
16 kB
subtitles/4 - 8 - Bayes Rule (1153).srt
16 kB
subtitles/9 - 3 - 03 Intuition for Logistic Regression and Support Vector Machines (1055).srt
16 kB
subtitles/8 - 6 - Example BigTable (1105).srt
16 kB
subtitles/4 - 1 - Statistics Intro (1036).srt
16 kB
subtitles/4 - 5 - Multiple Hypothesis Testing (1122).srt
16 kB
subtitles/2 - 4 - Relational Algebra Details Union Diff Select (1053).srt
15 kB
subtitles/2 - 5 - Relational Algebra Details Project Cross Product Equi-Join (1106).srt
15 kB
subtitles/8 - 5 - Example CouchDB (1000).srt
15 kB
subtitles/5 - 8 - 08 Evaluation and Cross-Validation (1046).srt
15 kB
subtitles/8 - 12 - Pig Evaluation (1011).srt
15 kB
subtitles/2 - 11 - Logical Data Independence (1123).srt
15 kB
subtitles/4 - 4 - Fraud and Benfords Law (1055).srt
14 kB
subtitles/4 - 3 - Effect Size Meta-analysis Heteroskedasticity (931).srt
14 kB
subtitles/5 - 5 - 05 Decision Trees Entropy (1051).srt
14 kB
subtitles/2 - 10 - Declarative Languages (1030).srt
14 kB
subtitles/8 - 4 - Example Dynamo (1016).srt
14 kB
subtitles/2 - 2 - Motivating Relational Algebra (857).srt
13 kB
subtitles/5 - 10 - 10 Ensembles Bagging and Boosting (0919).srt
13 kB
subtitles/9 - 5 - 05 Stochastic Gradient Descent Minibatches Parallelization (0853).srt
13 kB
subtitles/8 - 1 - NoSQL Introduction (830).srt
13 kB
subtitles/9 - 8 - 08 DBSCAN (0913).srt
13 kB
subtitles/3 - 5 - MapReduce Text Examples (958).srt
13 kB
subtitles/1 - 9 - Guest Lecture Biomedical Informatics (1024).srt
13 kB
subtitles/5 - 3 - 03 Rules Part 1 (0919).srt
13 kB
subtitles/6 - 2 - 02 Data Types (937).srt
13 kB
subtitles/2 - 6 - Relational Algebra Details Theta-Join (834).srt
12 kB
subtitles/5 - 1 - 01 Introduction to Machine Learning Part 1 (0754).srt
12 kB
subtitles/1 - 10 - Logistics (742).srt
12 kB
subtitles/4 - 2 - Publication Bias (845).srt
12 kB
subtitles/9 - 1 - 01 Gradient Descent Part 1 (0718).srt
11 kB
subtitles/2 - 8 - SQL for Data Science User-Defined Functions (759).srt
11 kB
subtitles/3 - 10 - Comparing MapReduce and Databases (0639).srt
11 kB
subtitles/4 - 7 - Bayesian Intro (759).srt
11 kB
subtitles/9 - 4 - 04 Intuition for Regularization (0659).srt
10 kB
subtitles/3 - 4 - MapReduce Pseudocode (754).srt
10 kB
subtitles/9 - 6 - 06 Unsupervised Learning (0611).srt
10 kB
subtitles/3 - 7 - MapReduce Matrix Multiply Example (931).srt
10 kB
subtitles/6 - 1 - 01 Introduction (717).srt
9.9 kB
subtitles/9 - 2 - 02 Gradient Descent Part 2 (0629).srt
9.1 kB
subtitles/5 - 2 - 02 Introduction to Machine Learning Part 2 (0523).srt
8.0 kB
subtitles/6 - 5 - 05 Visual Encoding (Part 1) (638).srt
7.8 kB
subtitles/5 - 4 - 04 Rules Part 2 (0539).srt
7.5 kB
subtitles/9 - 7 - 07 K-means (0556).srt
7.3 kB
subtitles/6 - 7 - 07 Visual Perception (Part 1) (439).srt
6.2 kB
subtitles/5 - 9 - 09 The Bootstrap (0413).srt
5.9 kB
subtitles/6 - 8 - 08 Visual Perception (Part 2) (418).srt
5.2 kB
subtitles/6 - 3 - 03 Data Types (Exercises) (407).srt
4.9 kB
subtitles/6 - 9 - 09 Visual Perception (Part 3) (356).srt
4.4 kB
subtitles/6 - 10 - 10 Evaluation (325).srt
4.2 kB
subtitles/6 - 4 - 04 Data Dimensions (308).srt
3.9 kB
subtitles/6 - 6 - 06 Visual Encoding (Part 2) (254).srt
3.5 kB
virtual machine/tips.txt
856 B