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Applied Data Science with Python
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[TutsNode.com] - Applied Data Science with Python
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python-social-network-analysis
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04_network-evolution
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01_module-4-applications
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03_small-world-networks.mp4 - 53.03 MB
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04_link-prediction.mp4 - 42.14 MB
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01_preferential-attachment-model.mp4 - 29.29 MB
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02_power-laws-and-rich-get-richer-phenomena-optional_networks-book-ch18.pdf - 311.95 KB
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01_preferential-attachment-model.en.srt - 18.44 KB
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02_power-laws-and-rich-get-richer-phenomena-optional_instructions.html - 1.4 KB
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03_small-world-networks.en.srt - 30.04 KB
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04_link-prediction.en.srt - 27.71 KB
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06_the-small-world-phenomenon-optional_instructions.html - 1.57 KB
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06_the-small-world-phenomenon-optional_networks-book-ch02.pdf - 2.07 MB
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06_the-small-world-phenomenon-optional_networks-book-ch20.pdf - 1.53 MB
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05_module-4-quiz_exam.html - 669.93 KB
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03_post-course-survey
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01_post-course-survey_instructions.html - 1.7 KB
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02_keep-learning-with-michigan-online_instructions.html - 34.14 KB
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02_module-4-assignment
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01_assignment-4-submission_instructions.html - 1.05 KB
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01_why-study-networks-and-basics-on-networkx
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01_module-1-why-study-networks-and-basics-on-networkx
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06_bipartite-graphs.en.srt - 18.59 KB
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09_module-1-quiz_exam.html - 488.89 KB
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01_course-syllabus_instructions.html - 11.43 KB
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05_node-and-edge-attributes.en.srt - 12.65 KB
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06_bipartite-graphs.mp4 - 22.41 MB
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02_help-us-learn-more-about-you_instructions.html - 1.86 KB
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07_notice-for-auditing-learners-assignment-submission_instructions.html - 1.61 KB
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04_network-definition-and-vocabulary.en.srt - 14.21 KB
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03_networks-definition-and-why-we-study-them.en.srt - 10.78 KB
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08_ta-demonstration-loading-graphs-in-networkx.en.srt - 10.43 KB
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04_network-definition-and-vocabulary.mp4 - 17.76 MB
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03_networks-definition-and-why-we-study-them.mp4 - 15.37 MB
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05_node-and-edge-attributes.mp4 - 15.09 MB
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08_ta-demonstration-loading-graphs-in-networkx.mp4 - 11.68 MB
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02_module-1-assignment
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01_assignment-1-submission_instructions.html - 1.07 KB
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03_influence-measures-and-network-centralization
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01_module-3-influence-measures-and-network-centralization
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02_betweenness-centrality.mp4 - 26.4 MB
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05_hubs-and-authorities.mp4 - 26.22 MB
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07_module-3-quiz_exam.html - 282.97 KB
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06_centrality-examples.en.srt - 13.79 KB
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02_betweenness-centrality.en.srt - 24.61 KB
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01_degree-and-closeness-centrality.mp4 - 21.43 MB
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05_hubs-and-authorities.en.srt - 18.97 KB
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01_degree-and-closeness-centrality.en.srt - 18.37 KB
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03_basic-page-rank.en.srt - 14.08 KB
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04_scaled-page-rank.en.srt - 13.58 KB
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04_scaled-page-rank.mp4 - 18.74 MB
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03_basic-page-rank.mp4 - 17.67 MB
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06_centrality-examples.mp4 - 16.79 MB
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02_module-3-assignment
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01_assignment-3-submission_instructions.html - 1.05 KB
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05_Resources
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02_additional-resources
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01__classes.html - 90.23 KB
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01__Scikit_Learn_Cheat_Sheet_Python.pdf - 145.68 KB
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01__documentation.html - 582 B
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01__resources.html - 2.19 KB
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05_attributions-credits
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01__resources.html - 997 B
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03_code-sharing-policy
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01__resources.html - 1.75 KB
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04_lecture-slides
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01__resources.html - 2.93 KB
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01__3.5_Hubs_and_Authorities.pdf - 14.63 MB
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01__1.1_Networks_Everywhere.pdf - 7.71 MB
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01__3.3_Basic_Page_Rank.pdf - 6.77 MB
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01__2.4_Network_Robustness.pdf - 6.66 MB
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01__3.6_Centrality_Examples.pdf - 6.32 MB
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01__4.3_Link_Prediction.pdf - 5.94 MB
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01__4.2_Small_World_Networks.pdf - 5 MB
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01__4.1_Preferential_Attachment_Model.pdf - 4.37 MB
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01__2.3_Connected_Components.pdf - 3.4 MB
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01__3.4_Scaled_Page_Rank.pdf - 3.38 MB
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01__3.2_Betweenness_Centrality.pdf - 2.74 MB
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01__1.2_Network_Definition_and_Vocabulary.pdf - 2.68 MB
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01__2.1_Clustering_Coefficient.pdf - 2.58 MB
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01__2.2_Distance_Measures.pdf - 2.24 MB
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01__3.1_Degree_and_Closeness_Centrality.pdf - 2.18 MB
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01__1.4_Bipartite_Graphs.pdf - 2.01 MB
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01__1.3_Node_and_Edge_Attributes.pdf - 1.51 MB
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01_jupyter-notebook-faq
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01__resources.html - 700.6 KB
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02_network-connectivity
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01_module-2-network-connectivity
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03_connected-components.en.srt - 14.58 KB
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02_distance-measures.mp4 - 26.06 MB
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02_distance-measures.en.srt - 26.06 KB
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01_clustering-coefficient.en.srt - 19.38 KB
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04_network-robustness.en.srt - 14.94 KB
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04_network-robustness.mp4 - 18.91 MB
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01_clustering-coefficient.mp4 - 18.69 MB
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05_ta-demonstration-simple-network-visualizations-in-networkx.en.srt - 7.33 KB
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03_connected-components.mp4 - 15.54 MB
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05_ta-demonstration-simple-network-visualizations-in-networkx.mp4 - 10.09 MB
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06_module-2-quiz_exam.html - 1.08 MB
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02_module-2-assignment
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01_assignment-2-submission_instructions.html - 1.05 KB
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python-plotting
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05_Resources
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03_course-slides
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01__Week2_Slides_Final.pdf - 482.41 KB
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01__Week3Slides.pptx - 359.34 KB
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01__Week2_Basic_Charting.pptx - 238.71 KB
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01__resources.html - 1.73 KB
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01__Week1Slides.pptx - 15.54 MB
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01__Week1_Slides_Final.pdf - 4.17 MB
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01__Week3_Slides_Final.pdf - 525.63 KB
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02_additional-python-resources
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01__classes.html - 90.23 KB
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01__resources.html - 1.75 KB
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04_acknowledgements-credits
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01__Diamonds-Were-a-Girls-Best-Friend.jpg - 146.83 KB
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01__hist.pdf - 116.4 KB
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01__matplotlib.html - 42.28 KB
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01__resources.html - 6.08 KB
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06_accessible-html-slides
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01__Week_1_Principles_of_Information_Visualization.html - 84.89 KB
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01__Week_2_Basic_Charting.html - 73.48 KB
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01__Week_3_Charting_Fundamentals.html - 73.04 KB
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01__resources.html - 1.34 KB
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05_code-sharing-policy
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01__resources.html - 1.75 KB
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01_jupyter-notebook-faq
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01__resources.html - 523.18 KB
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01_module-1-principles-of-information-visualization
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01_principles-of-information-visualization
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01_introduction.en.srt - 6.6 KB
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11_graphical-heuristics-lie-factor-and-spark-lines-edward-tufte.en.srt - 5.38 KB
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03_help-us-learn-more-about-you_instructions.html - 1.66 KB
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04_about-the-professor-christopher-brooks.en.srt - 2.1 KB
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06_notice-for-coursera-learners-assignment-submission_instructions.html - 1.61 KB
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08_dark-horse-analytics-optional_instructions.html - 1.3 KB
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12_the-truthful-art-alberto-cairo.mp4 - 19.54 MB
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12_the-truthful-art-alberto-cairo.en.srt - 12.63 KB
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05_tools-for-thinking-about-design-alberto-cairo.mp4 - 19.22 MB
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05_tools-for-thinking-about-design-alberto-cairo.en.srt - 12.58 KB
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02_syllabus_instructions.html - 11.63 KB
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10_useful-junk-the-effects-of-visual-embellishment-on-comprehension-and_instructions.html - 1.33 KB
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09_graphical-heuristics-chart-junk-edward-tufte.en.srt - 7.64 KB
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07_graphical-heuristics-data-ink-ratio-edward-tufte.en.srt - 6.97 KB
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09_graphical-heuristics-chart-junk-edward-tufte.mp4 - 13.14 MB
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01_introduction.mp4 - 12.09 MB
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07_graphical-heuristics-data-ink-ratio-edward-tufte.mp4 - 9.24 MB
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11_graphical-heuristics-lie-factor-and-spark-lines-edward-tufte.mp4 - 8.67 MB
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04_about-the-professor-christopher-brooks.mp4 - 5.49 MB
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02_assignment-1
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01_graphics-lies-misleading-visuals_BookChapterLIES.pdf - 333.4 KB
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02_graphics-lies-misleading-visuals_assignment1_rubric.pdf - 72.72 KB
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01_graphics-lies-misleading-visuals_instructions.html - 1.38 KB
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02_graphics-lies-misleading-visuals_peer_assignment_instructions.html - 3.17 KB
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02_module-2-basic-charting
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01_module-2-basic-charting
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08_bar-charts.en.srt - 5.49 KB
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03_matplotlib_matplotlib.html - 42.28 KB
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04_ten-simple-rules-for-better-figures_instructions.html - 1.48 KB
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05_basic-plotting-with-matplotlib.en.srt - 11.87 KB
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07_line-plots.en.srt - 11.8 KB
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06_scatterplots.en.srt - 11.51 KB
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02_matplotlib-architecture.en.srt - 10.22 KB
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03_matplotlib_instructions.html - 1.36 KB
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09_dejunkifying-a-plot.en.srt - 5.89 KB
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01_introduction.en.srt - 2.63 KB
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06_scatterplots.mp4 - 17.65 MB
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02_matplotlib-architecture.mp4 - 16.37 MB
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07_line-plots.mp4 - 15.77 MB
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05_basic-plotting-with-matplotlib.mp4 - 14.06 MB
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09_dejunkifying-a-plot.mp4 - 12.24 MB
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08_bar-charts.mp4 - 9.29 MB
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01_introduction.mp4 - 4.21 MB
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02_assignment-2
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01_plotting-weather-patterns_assignment2_rubric.pdf - 75.27 KB
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01_plotting-weather-patterns_peer_assignment_instructions.html - 1.8 KB
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03_module-3-charting-fundamentals
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01_module-3-charting-fundamentals
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03_selecting-the-number-of-bins-in-a-histogram-a-decision-theoretic-approach_hist.pdf - 116.4 KB
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03_selecting-the-number-of-bins-in-a-histogram-a-decision-theoretic-approach_instructions.html - 1.19 KB
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07_interactivity.en.srt - 7.37 KB
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02_histograms.en.srt - 12.15 KB
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01_subplots.en.srt - 10.54 KB
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04_box-plots.en.srt - 10.34 KB
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06_animation.en.srt - 7.08 KB
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05_heatmaps.en.srt - 5.33 KB
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02_histograms.mp4 - 17.05 MB
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01_subplots.mp4 - 15.44 MB
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04_box-plots.mp4 - 14.52 MB
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07_interactivity.mp4 - 10.21 MB
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06_animation.mp4 - 9.05 MB
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05_heatmaps.mp4 - 7.65 MB
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02_assignment-3
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02_building-a-custom-visualization_assignment3_rubric.pdf - 73.64 KB
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02_building-a-custom-visualization_peer_assignment_instructions.html - 1.74 KB
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01_assignment-reading_instructions.html - 1.46 KB
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04_module-4-applied-visualizations
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02_project
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02_becoming-an-independent-data-scientist_assignment4_rubric.pdf - 85.64 KB
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01_becoming-an-independent-data-scientist.en.srt - 2.63 KB
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02_becoming-an-independent-data-scientist_peer_assignment_instructions.html - 1.89 KB
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03_post-course-survey_instructions.html - 1.5 KB
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01_becoming-an-independent-data-scientist.mp4 - 4.51 MB
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01_module-4-applied-visualizations
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03_spurious-correlations_instructions.html - 1.65 KB
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02_seaborn.en.srt - 11.31 KB
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01_plotting-with-pandas.en.srt - 9.54 KB
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02_seaborn.mp4 - 12.5 MB
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01_plotting-with-pandas.mp4 - 10.58 MB
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python-machine-learning
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01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn
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01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn
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03_help-us-learn-more-about-you_instructions.html - 1.66 KB
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06_notice-for-auditing-learners-assignment-submission_instructions.html - 1.61 KB
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10_zachary-lipton-the-foundations-of-algorithmic-bias-optional_instructions.html - 1.97 KB
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09_k-nearest-neighbors-classification.mp4 - 26.9 MB
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04_key-concepts-in-machine-learning.mp4 - 23.8 MB
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11_module-1-quiz_exam.html - 180.34 KB
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01_course-syllabus_0636920030515.do - 73.22 KB
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09_k-nearest-neighbors-classification.en.srt - 26.19 KB
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07_an-example-machine-learning-problem.mp4 - 19.1 MB
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04_key-concepts-in-machine-learning.en.srt - 18.82 KB
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02_introduction.en.srt - 16.07 KB
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07_an-example-machine-learning-problem.en.srt - 14.83 KB
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01_course-syllabus_instructions.html - 12.51 KB
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08_examining-the-data.en.srt - 12.05 KB
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05_python-tools-for-machine-learning.en.srt - 6.11 KB
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02_introduction.mp4 - 17.49 MB
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08_examining-the-data.mp4 - 15.67 MB
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05_python-tools-for-machine-learning.mp4 - 7.75 MB
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02_assignment-1
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01_assignment-1-submission_instructions.html - 1.06 KB
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03_module-3-evaluation
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01_module-3-evaluation
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01_model-evaluation-selection.mp4 - 31.76 MB
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07_practical-guide-to-controlled-experiments-on-the-web-optional_2007GuideControlledExperiments.pdf - 493.03 KB
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07_practical-guide-to-controlled-experiments-on-the-web-optional_instructions.html - 1.77 KB
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06_regression-evaluation.en.srt - 7.83 KB
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09_module-3-quiz_exam.html - 202.86 KB
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08_model-selection-optimizing-classifiers-for-different-evaluation-metrics.mp4 - 20.02 MB
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01_model-evaluation-selection.en.srt - 30.08 KB
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08_model-selection-optimizing-classifiers-for-different-evaluation-metrics.en.srt - 18.12 KB
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02_confusion-matrices-basic-evaluation-metrics.en.srt - 15.85 KB
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05_multi-class-evaluation.en.srt - 15.21 KB
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03_classifier-decision-functions.en.srt - 9.04 KB
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04_precision-recall-and-roc-curves.en.srt - 7.53 KB
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05_multi-class-evaluation.mp4 - 16.72 MB
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02_confusion-matrices-basic-evaluation-metrics.mp4 - 16.19 MB
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03_classifier-decision-functions.mp4 - 9.91 MB
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06_regression-evaluation.mp4 - 9.65 MB
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04_precision-recall-and-roc-curves.mp4 - 8.09 MB
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02_assignment-3
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01_assignment-3-submission_instructions.html - 1.05 KB
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05_Resources
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01_additional-resources
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01__classes.html - 90.23 KB
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01__resources.html - 2.1 KB
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01__Scikit_Learn_Cheat_Sheet_Python.pdf - 145.68 KB
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01__documentation.html - 582 B
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03_course-slides
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01__resources.html - 1.83 KB
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01__02-adspy-module2-supervised1.pdf - 5.1 MB
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01__01-adspy-module1-basics.pdf - 3.13 MB
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01__05-adspy-unsupervised.pdf - 2.42 MB
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01__04-adspy-module4-supervised2.pdf - 2.29 MB
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01__03-adspy-module3-evaluation.pdf - 1.77 MB
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04_code-sharing-policy
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01__resources.html - 1.75 KB
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05_attributions-credits
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01__resources.html - 996 B
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02_jupyter-notebook-faq
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01__resources.html - 701.18 KB
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02_module-2-supervised-machine-learning-part-1
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01_module-2-supervised-machine-learning
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01_introduction-to-supervised-machine-learning.en.srt - 22.13 KB
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06_linear-regression-ridge-lasso-and-polynomial-regression.mp4 - 29.31 MB
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12_decision-trees.mp4 - 27.49 MB
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10_kernelized-support-vector-machines.mp4 - 26.69 MB
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13_a-few-useful-things-to-know-about-machine-learning_instructions.html - 1.6 KB
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14_ed-yong-genetic-test-for-autism-refuted-optional_instructions.html - 1.67 KB
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01_introduction-to-supervised-machine-learning.mp4 - 24.94 MB
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08_linear-classifiers-support-vector-machines.en.srt - 15.54 KB
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05_linear-regression-least-squares.mp4 - 23.92 MB
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07_logistic-regression.en.srt - 17.13 KB
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04_k-nearest-neighbors-classification-and-regression.en.srt - 17.09 KB
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11_cross-validation.en.srt - 13 KB
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12_decision-trees.en.srt - 28.36 KB
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06_linear-regression-ridge-lasso-and-polynomial-regression.en.srt - 27.19 KB
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10_kernelized-support-vector-machines.en.srt - 25.6 KB
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05_linear-regression-least-squares.en.srt - 21.26 KB
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02_overfitting-and-underfitting.en.srt - 15.81 KB
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09_multi-class-classification.en.srt - 8.3 KB
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03_supervised-learning-datasets.en.srt - 6.74 KB
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08_linear-classifiers-support-vector-machines.mp4 - 18.32 MB
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04_k-nearest-neighbors-classification-and-regression.mp4 - 17.81 MB
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07_logistic-regression.mp4 - 16.45 MB
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02_overfitting-and-underfitting.mp4 - 15.57 MB
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13_a-few-useful-things-to-know-about-machine-learning_cacm12.pdf - 15.12 MB
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11_cross-validation.mp4 - 12.92 MB
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09_multi-class-classification.mp4 - 9.92 MB
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03_supervised-learning-datasets.mp4 - 7.27 MB
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15_module-2-quiz_exam.html - 554.29 KB
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02_assignment-2
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01_assignment-2-submission_instructions.html - 1.05 KB
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04_module-4-supervised-machine-learning-part-2
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01_module-4-supervised-machine-learning-part-2
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04_neural-networks.mp4 - 27.09 MB
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05_neural-networks-made-easy-optional_instructions.html - 1.52 KB
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06_play-with-neural-networks-tensorflow-playground-optional_instructions.html - 2 KB
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08_deep-learning-in-a-nutshell-core-concepts-optional_instructions.html - 1.56 KB
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14_rules-of-machine-learning-best-practices-for-ml-engineering-optional_rules_of_ml.pdf - 449.46 KB
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09_assisting-pathologists-in-detecting-cancer-with-deep-learning-optional_instructions.html - 1.31 KB
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11_the-treachery-of-leakage-optional_instructions.html - 1.36 KB
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12_leakage-in-data-mining-formulation-detection-and-avoidance-optional_instructions.html - 1.72 KB
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13_data-leakage-example-the-icml-2013-whale-challenge-optional_instructions.html - 1.59 KB
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14_rules-of-machine-learning-best-practices-for-ml-engineering-optional_instructions.html - 1.55 KB
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09_assisting-pathologists-in-detecting-cancer-with-deep-learning-optional_assisting-pathologists-in-detecting.html - 141.99 KB
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10_data-leakage.mp4 - 19.14 MB
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04_neural-networks.en.srt - 27.9 KB
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02_random-forests.en.srt - 17.07 KB
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10_data-leakage.en.srt - 16.69 KB
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01_naive-bayes-classifiers.en.srt - 11.2 KB
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07_deep-learning-optional.en.srt - 10.34 KB
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03_gradient-boosted-decision-trees.en.srt - 8.44 KB
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02_random-forests.mp4 - 17.39 MB
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01_naive-bayes-classifiers.mp4 - 12.3 MB
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07_deep-learning-optional.mp4 - 10.76 MB
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03_gradient-boosted-decision-trees.mp4 - 8.47 MB
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15_module-4-quiz_exam.html - 1.6 MB
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12_leakage-in-data-mining-formulation-detection-and-avoidance-optional_cs670_Tran_PreferredPaper_LeakingInDataMining.pdf - 847.57 KB
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02_assignment-4
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01_assignment-4-submission_instructions.html - 1.05 KB
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03_optional-unsupervised-machine-learning
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04_how-to-use-t-sne-effectively_instructions.html - 1.16 KB
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05_how-machines-make-sense-of-big-data-an-introduction-to-clustering-algorithms_instructions.html - 1.32 KB
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03_clustering.mp4 - 19.83 MB
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03_clustering.en.srt - 19.9 KB
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02_dimensionality-reduction-and-manifold-learning.en.srt - 13.47 KB
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01_introduction.en.srt - 6.46 KB
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02_dimensionality-reduction-and-manifold-learning.mp4 - 12.88 MB
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01_introduction.mp4 - 6.66 MB
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04_conclusion
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03_keep-learning-with-michigan-online_instructions.html - 34.14 KB
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02_post-course-survey_instructions.html - 1.51 KB
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01_conclusion.en.srt - 3.9 KB
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01_conclusion.mp4 - 4.49 MB
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python-text-mining
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05_Resources
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04_lecture-slides
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01__1.2_Handling_Text_in_Python.pdf - 242.52 KB
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01__3.4_Naive_Bayes_Variations.pdf - 210.48 KB
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01__2.3_Advanced_NLP_Tasks_with_NLTK.pdf - 309.47 KB
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InfoHash:
C9EF88CFE0137F6A4292823F0765A5D4B93FF313
Last updated:
Aug 10, 2023
File count:
665 B
File Category:
9
Tags:
Other, Tutorials