Coursera Applied Data Science with Python

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Files
  1. 03_small-world-networks.mp453.0 MB
  2. TutsNode.com.txt63 bytes
  3. 01__Week2_Slides_Final.pdf482.4 KB
  4. 0203 bytes
  5. 04_link-prediction.mp442.1 MB
  6. 01__Week3Slides.pptx359.3 KB
  7. 03_help-us-learn-more-about-you_instructions.html1.7 KB
  8. 01_introduction.en.srt6.6 KB
  9. 179 bytes
  10. 01_model-evaluation-selection.mp431.8 MB
  11. 01__1.2_Handling_Text_in_Python.pdf242.5 KB
  12. 06_notice-for-auditing-learners-assignment-submission_instructions.html1.6 KB
  13. 01_week-3-a-conversation-with-andrew-ng.en.srt5.1 KB
  14. 259 bytes
  15. 05_support-vector-machines.mp431.4 MB
  16. 01__classes.html90.2 KB
  17. 01_introduction-to-supervised-machine-learning.en.srt22.1 KB
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  19. 06_linear-regression-ridge-lasso-and-polynomial-regression.mp429.3 MB
  20. 10_resources-common-issues-with-free-text_re.html196.3 KB
  21. 01_assignment-1-submission_instructions.html1.1 KB
  22. 07_practical-guide-to-controlled-experiments-on-the-web-optional_2007GuideControlledExperiments.pdf493.0 KB
  23. 06_bipartite-graphs.en.srt18.6 KB
  24. 497 bytes
  25. 01_preferential-attachment-model.mp429.3 MB
  26. 01__3.4_Naive_Bayes_Variations.pdf210.5 KB
  27. 06_lstm.en.srt2.5 KB
  28. 56 bytes
  29. 12_decision-trees.mp427.5 MB
  30. 08_bar-charts.en.srt5.5 KB
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  32. 04_neural-networks.mp427.1 MB
  33. 10_zachary-lipton-the-foundations-of-algorithmic-bias-optional_instructions.html2.0 KB
  34. 06_additional-resources-readings_blei03a.pdf408.2 KB
  35. 11_graphical-heuristics-lie-factor-and-spark-lines-edward-tufte.en.srt5.4 KB
  36. 7366 bytes
  37. 09_k-nearest-neighbors-classification.mp426.9 MB
  38. 01__classes.html90.2 KB
  39. 15_week-2-quiz_exam.html11.0 KB
  40. 8172 bytes
  41. 05_information-extraction.mp426.7 MB
  42. 02_power-laws-and-rich-get-richer-phenomena-optional_networks-book-ch18.pdf312.0 KB
  43. 06_additional-resources-readings_instructions.html2.1 KB
  44. 93 bytes
  45. 10_kernelized-support-vector-machines.mp426.7 MB
  46. 01__2.3_Advanced_NLP_Tasks_with_NLTK.pdf309.5 KB
  47. 13_a-few-useful-things-to-know-about-machine-learning_instructions.html1.6 KB
  48. 14_ed-yong-genetic-test-for-autism-refuted-optional_instructions.html1.7 KB
  49. 04_practice-quiz_quiz.html2.4 KB
  50. 01_assignment-2-submission_instructions.html1.0 KB
  51. 09_module-1-quiz_exam.html488.9 KB
  52. 01_semantic-text-similarity.en.srt21.3 KB
  53. [TGx]Downloaded from torrentgalaxy.to .txt585 bytes
  54. 10277 bytes
  55. 02_betweenness-centrality.mp426.4 MB
  56. 01__classes.html90.2 KB
  57. 01_time-series-examples.en.srt7.3 KB
  58. 1127 bytes
  59. 03_naive-bayes-classifiers.mp426.4 MB
  60. 03_selecting-the-number-of-bins-in-a-histogram-a-decision-theoretic-approach_hist.pdf116.4 KB
  61. 03_connected-components.en.srt14.6 KB
  62. 1251 bytes
  63. 05_hubs-and-authorities.mp426.2 MB
  64. 07_practical-guide-to-controlled-experiments-on-the-web-optional_instructions.html1.8 KB
  65. 07_module-3-quiz_exam.html283.0 KB
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  67. 02_distance-measures.mp426.1 MB
  68. 01_assignment-3-submission_instructions.html1.0 KB
  69. 01__4.2_Topic_Modeling.pdf446.6 KB
  70. 02_help-us-learn-more-about-you_instructions.html1.8 KB
  71. 1411 bytes
  72. 01_introduction-to-supervised-machine-learning.mp424.9 MB
  73. 01__intro.html42.8 KB
  74. 08_linear-classifiers-support-vector-machines.en.srt15.5 KB
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  76. 05_linear-regression-least-squares.mp423.9 MB
  77. 05_neural-networks-made-easy-optional_instructions.html1.5 KB
  78. 06_play-with-neural-networks-tensorflow-playground-optional_instructions.html2.0 KB
  79. 01_plotting-weather-patterns_assignment2_rubric.pdf75.3 KB
  80. 01_post-course-survey_instructions.html1.7 KB
  81. 08_deep-learning-in-a-nutshell-core-concepts-optional_instructions.html1.6 KB
  82. 14_rules-of-machine-learning-best-practices-for-ml-engineering-optional_rules_of_ml.pdf449.5 KB
  83. 09_assisting-pathologists-in-detecting-cancer-with-deep-learning-optional_instructions.html1.3 KB
  84. 03_matplotlib_matplotlib.html42.3 KB
  85. 07_logistic-regression.en.srt17.1 KB
  86. 11_the-treachery-of-leakage-optional_instructions.html1.4 KB
  87. 01__4.1_Semantic_Text_Similarity.pdf414.5 KB
  88. 12_leakage-in-data-mining-formulation-detection-and-avoidance-optional_instructions.html1.7 KB
  89. 13_data-leakage-example-the-icml-2013-whale-challenge-optional_instructions.html1.6 KB
  90. 14_rules-of-machine-learning-best-practices-for-ml-engineering-optional_instructions.html1.6 KB
  91. 01__classes.html90.2 KB
  92. 02_congratulations.en.srt1.3 KB
  93. 01_assignment-4-submission_instructions.html1.0 KB
  94. 01__3.1_Text_Classification.pdf350.2 KB
  95. 01__Diamonds-Were-a-Girls-Best-Friend.jpg?042148146.8 KB
  96. 06_centrality-examples.en.srt13.8 KB
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  98. 04_key-concepts-in-machine-learning.mp423.8 MB
  99. 11_module-1-quiz_exam.html180.3 KB
  100. 04_how-to-use-t-sne-effectively_instructions.html1.2 KB
  101. 05_how-machines-make-sense-of-big-data-an-introduction-to-clustering-algorithms_instructions.html1.3 KB
  102. 01_preferential-attachment-model.en.srt18.4 KB
  103. 17363 bytes
  104. 02_basic-nlp-tasks-with-nltk.mp423.5 MB
  105. 01_course-syllabus_instructions.html11.4 KB
  106. 1810 bytes
  107. 04_handling-text-in-python.mp423.4 MB
  108. 01__resources.html2.1 KB
  109. 01__hist.pdf116.4 KB
  110. 04_handling-text-in-python.en.srt22.6 KB
  111. 07_lstm-notebook_instructions.html1.2 KB
  112. 195 bytes
  113. 03_generative-models-and-lda.mp423.2 MB
  114. 01_graphics-lies-misleading-visuals_BookChapterLIES.pdf333.4 KB
  115. 02_power-laws-and-rich-get-richer-phenomena-optional_instructions.html1.4 KB
  116. 01__resources.html1.8 KB
  117. 01__resources.html1.8 KB
  118. 01__resources.html996 bytes
  119. 01__3.6_Learning_Text_Classifiers_in_Python.pdf349.0 KB
  120. 01__Scikit_Learn_Cheat_Sheet_Python.pdf145.7 KB
  121. 05_node-and-edge-attributes.en.srt12.6 KB
  122. 03_help-us-learn-more-about-you_instructions.html1.7 KB
  123. 04_about-the-professor-christopher-brooks.en.srt2.1 KB
  124. 01__3.3_Naive_Bayes_Classifier.pdf261.5 KB
  125. 01__Week2_Basic_Charting.pptx238.7 KB
  126. 06_regression-evaluation.en.srt7.8 KB
  127. 06_notice-for-coursera-learners-assignment-submission_instructions.html1.6 KB
  128. 01__1.3_Regular_Expressions.pdf258.5 KB
  129. 01__2.2_Basic_NLP_Tasks_with_NLTK.pdf230.5 KB
  130. 08_dark-horse-analytics-optional_instructions.html1.3 KB
  131. 06_regular-expressions.en.srt20.2 KB
  132. 20143 bytes
  133. 06_regular-expressions.mp422.6 MB
  134. 01__2.1_Basic_Natural_Language_Processing.pdf223.3 KB
  135. 01__3.2_Identifying_Features_from_Text.pdf215.8 KB
  136. 04_k-nearest-neighbors-classification-and-regression.en.srt17.1 KB
  137. 01__resources.html997 bytes
  138. 2112 bytes
  139. 01_semantic-text-similarity.mp422.5 MB
  140. 02_betweenness-centrality.en.srt24.6 KB
  141. 22574 bytes
  142. 06_bipartite-graphs.mp422.4 MB
  143. 02_becoming-an-independent-data-scientist_assignment4_rubric.pdf85.6 KB
  144. 01_a-conversation-with-andrew-ng.en.srt2.5 KB
  145. 2327 bytes
  146. 03_advanced-nlp-tasks-with-nltk.mp421.8 MB
  147. 09_module-3-quiz_exam.html202.9 KB
  148. 04_ten-simple-rules-for-better-figures_instructions.html1.5 KB
  149. 02_basic-nlp-tasks-with-nltk.en.srt20.9 KB
  150. 24141 bytes
  151. 01_degree-and-closeness-centrality.mp421.4 MB
  152. 11_forecasting-notebook_SP_Week_1_-_Lesson_3_-_Notebook.ipynb66.9 KB
  153. 07_module-4-quiz_exam.html4.9 KB
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  155. 06_learning-text-classifiers-in-python.mp420.3 MB
  156. 01__Scikit_Learn_Cheat_Sheet_Python.pdf145.7 KB
  157. 14_lstm-notebook_SP_Week_3_Lesson_4_-_LSTM.ipynb66.9 KB
  158. 06_adjusting-the-learning-rate-dynamically.en.srt4.3 KB
  159. 269 bytes
  160. 08_model-selection-optimizing-classifiers-for-different-evaluation-metrics.mp420.0 MB
  161. 01__Scikit_Learn_Cheat_Sheet_Python.pdf145.7 KB
  162. 09_assisting-pathologists-in-detecting-cancer-with-deep-learning-optional_assisting-pathologists-in-detecting.html142.0 KB
  163. 01__Week_1_Principles_of_Information_Visualization.html84.9 KB
  164. 02_building-a-custom-visualization_assignment3_rubric.pdf73.6 KB
  165. 01__matplotlib.html42.3 KB
  166. 03_selecting-the-number-of-bins-in-a-histogram-a-decision-theoretic-approach_instructions.html1.2 KB
  167. 11_sunspots.en.srt2.4 KB
  168. 27163 bytes
  169. 03_clustering.mp419.8 MB
  170. 01__Week_2_Basic_Charting.html73.5 KB
  171. 01_course-syllabus_0636920030515.do73.2 KB
  172. 03_naive-bayes-classifiers.en.srt22.6 KB
  173. 08_machine-learning-on-time-windows.en.srt1.0 KB
  174. 2813 bytes
  175. 12_the-truthful-art-alberto-cairo.mp419.5 MB
  176. 01__Week_3_Charting_Fundamentals.html73.0 KB
  177. 02_building-a-custom-visualization_peer_assignment_instructions.html1.7 KB
  178. 02_graphics-lies-misleading-visuals_assignment1_rubric.pdf72.7 KB
  179. 09_rnn-notebook_SP_Week_3_Lesson_2_-_RNN.ipynb66.9 KB
  180. 11_single-layer-neural-network-notebook_SP_Week_2_Lesson_2.ipynb66.8 KB
  181. 12_sunspots-notebook_SP_Week_4_Lesson_5.ipynb66.8 KB
  182. 03_spurious-correlations_instructions.html1.6 KB
  183. 01_becoming-an-independent-data-scientist.en.srt2.6 KB
  184. 04_preparing-features-and-labels-notebook_SP_Week_2_Lesson_1.ipynb66.8 KB
  185. 03_keep-learning-with-michigan-online_instructions.html34.1 KB
  186. 02_becoming-an-independent-data-scientist_peer_assignment_instructions.html1.9 KB
  187. 03_post-course-survey_instructions.html1.5 KB
  188. 12_the-truthful-art-alberto-cairo.en.srt12.6 KB
  189. 29348 bytes
  190. 05_tools-for-thinking-about-design-alberto-cairo.mp419.2 MB
  191. 01__resources.html1.7 KB
  192. 14_deep-neural-network-notebook_SP_Week_2_Lesson_3.ipynb66.8 KB
  193. 07_lstm-notebook_SP_Week_4_Lesson_1.ipynb66.8 KB
  194. 12_sunspots-notebook_SP_Week_4_Lesson_3.ipynb66.8 KB
  195. 05_introduction-to-time-series-notebook_SP_Week_1_Lesson_2.ipynb66.8 KB
  196. 11_cross-validation.en.srt13.0 KB
  197. 30237 bytes
  198. 10_data-leakage.mp419.1 MB
  199. 02_keep-learning-with-michigan-online_instructions.html34.1 KB
  200. 02_keep-learning-with-michigan-online_instructions.html34.1 KB
  201. 05_support-vector-machines.en.srt32.0 KB
  202. 01__resources.html1.8 KB
  203. 01__resources.html1.3 KB
  204. 06_additional-resources-readings_wordnet.html31.0 KB
  205. 01_model-evaluation-selection.en.srt30.1 KB
  206. 03_small-world-networks.en.srt30.0 KB
  207. 12_decision-trees.en.srt28.4 KB
  208. 02_help-us-learn-more-about-you_instructions.html1.9 KB
  209. 04_neural-networks.en.srt27.9 KB
  210. 04_link-prediction.en.srt27.7 KB
  211. 06_linear-regression-ridge-lasso-and-polynomial-regression.en.srt27.2 KB
  212. 09_k-nearest-neighbors-classification.en.srt26.2 KB
  213. 02_distance-measures.en.srt26.1 KB
  214. 07_interactivity.en.srt7.4 KB
  215. 31120 bytes
  216. 07_an-example-machine-learning-problem.mp419.1 MB
  217. 07_notice-for-auditing-learners-assignment-submission_instructions.html1.6 KB
  218. 10_kernelized-support-vector-machines.en.srt25.6 KB
  219. 05_information-extraction.en.srt22.5 KB
  220. 05_linear-regression-least-squares.en.srt21.3 KB
  221. 01_assignment-1-submission_instructions.html1.1 KB
  222. 03_advanced-nlp-tasks-with-nltk.en.srt20.1 KB
  223. 06_learning-text-classifiers-in-python.en.srt19.9 KB
  224. 03_clustering.en.srt19.9 KB
  225. 01_clustering-coefficient.en.srt19.4 KB
  226. 01__resources.html1.8 KB
  227. 05_hubs-and-authorities.en.srt19.0 KB
  228. 04_key-concepts-in-machine-learning.en.srt18.8 KB
  229. 01_degree-and-closeness-centrality.en.srt18.4 KB
  230. 03_generative-models-and-lda.en.srt18.2 KB
  231. 08_model-selection-optimizing-classifiers-for-different-evaluation-metrics.en.srt18.1 KB
  232. 02_random-forests.en.srt17.1 KB
  233. 01_assignment-2-submission_instructions.html1.0 KB
  234. 10_data-leakage.en.srt16.7 KB
  235. 02_introduction.en.srt16.1 KB
  236. 02_confusion-matrices-basic-evaluation-metrics.en.srt15.8 KB
  237. 02_overfitting-and-underfitting.en.srt15.8 KB
  238. 05_multi-class-evaluation.en.srt15.2 KB
  239. 01_text-classification.en.srt15.2 KB
  240. 04_network-robustness.en.srt14.9 KB
  241. 07_an-example-machine-learning-problem.en.srt14.8 KB
  242. 04_network-definition-and-vocabulary.en.srt14.2 KB
  243. 02_identifying-features-from-text.en.srt9.6 KB
  244. 32276 bytes
  245. 04_network-robustness.mp418.9 MB
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  249. 09_internationalization-and-issues-with-non-ascii-characters.en.srt13.6 KB
  250. 02_dimensionality-reduction-and-manifold-learning.en.srt13.5 KB
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  254. 10_resources-common-issues-with-free-text_instructions.html1.9 KB
  255. 3318 bytes
  256. 04_scaled-page-rank.mp418.7 MB
  257. 06_the-small-world-phenomenon-optional_instructions.html1.6 KB
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  272. 03_networks-definition-and-why-we-study-them.en.srt10.8 KB
  273. 01_subplots.en.srt10.5 KB
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  288. 09_multi-class-classification.en.srt8.3 KB
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  290. 01_clustering-coefficient.mp418.7 MB
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