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Language:
English
Total Size:
1.9 GB
Info Hash:
C9EF88CFE0137F6A4292823F0765A5D4B93FF313
Added By:
Added:
July 1, 2023, 3:40 p.m.
Stats:
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(Last updated: May 17, 2025, 8:16 a.m.)
| File | Size |
|---|---|
| 03_small-world-networks.mp4 | 53.0 MB |
| TutsNode.com.txt | 63 bytes |
| 01__Week2_Slides_Final.pdf | 482.4 KB |
| 0 | 203 bytes |
| 04_link-prediction.mp4 | 42.1 MB |
| 01__Week3Slides.pptx | 359.3 KB |
| 03_help-us-learn-more-about-you_instructions.html | 1.7 KB |
| 01_introduction.en.srt | 6.6 KB |
| 1 | 79 bytes |
| 01_model-evaluation-selection.mp4 | 31.8 MB |
| 01__1.2_Handling_Text_in_Python.pdf | 242.5 KB |
| 06_notice-for-auditing-learners-assignment-submission_instructions.html | 1.6 KB |
| 01_week-3-a-conversation-with-andrew-ng.en.srt | 5.1 KB |
| 2 | 59 bytes |
| 05_support-vector-machines.mp4 | 31.4 MB |
| 01__classes.html | 90.2 KB |
| 01_introduction-to-supervised-machine-learning.en.srt | 22.1 KB |
| 3 | 36 bytes |
| 06_linear-regression-ridge-lasso-and-polynomial-regression.mp4 | 29.3 MB |
| 10_resources-common-issues-with-free-text_re.html | 196.3 KB |
| 01_assignment-1-submission_instructions.html | 1.1 KB |
| 07_practical-guide-to-controlled-experiments-on-the-web-optional_2007GuideControlledExperiments.pdf | 493.0 KB |
| 06_bipartite-graphs.en.srt | 18.6 KB |
| 4 | 97 bytes |
| 01_preferential-attachment-model.mp4 | 29.3 MB |
| 01__3.4_Naive_Bayes_Variations.pdf | 210.5 KB |
| 06_lstm.en.srt | 2.5 KB |
| 5 | 6 bytes |
| 12_decision-trees.mp4 | 27.5 MB |
| 08_bar-charts.en.srt | 5.5 KB |
| 6 | 86 bytes |
| 04_neural-networks.mp4 | 27.1 MB |
| 10_zachary-lipton-the-foundations-of-algorithmic-bias-optional_instructions.html | 2.0 KB |
| 06_additional-resources-readings_blei03a.pdf | 408.2 KB |
| 11_graphical-heuristics-lie-factor-and-spark-lines-edward-tufte.en.srt | 5.4 KB |
| 7 | 366 bytes |
| 09_k-nearest-neighbors-classification.mp4 | 26.9 MB |
| 01__classes.html | 90.2 KB |
| 15_week-2-quiz_exam.html | 11.0 KB |
| 8 | 172 bytes |
| 05_information-extraction.mp4 | 26.7 MB |
| 02_power-laws-and-rich-get-richer-phenomena-optional_networks-book-ch18.pdf | 312.0 KB |
| 06_additional-resources-readings_instructions.html | 2.1 KB |
| 9 | 3 bytes |
| 10_kernelized-support-vector-machines.mp4 | 26.7 MB |
| 01__2.3_Advanced_NLP_Tasks_with_NLTK.pdf | 309.5 KB |
| 13_a-few-useful-things-to-know-about-machine-learning_instructions.html | 1.6 KB |
| 14_ed-yong-genetic-test-for-autism-refuted-optional_instructions.html | 1.7 KB |
| 04_practice-quiz_quiz.html | 2.4 KB |
| 01_assignment-2-submission_instructions.html | 1.0 KB |
| 09_module-1-quiz_exam.html | 488.9 KB |
| 01_semantic-text-similarity.en.srt | 21.3 KB |
| [TGx]Downloaded from torrentgalaxy.to .txt | 585 bytes |
| 10 | 277 bytes |
| 02_betweenness-centrality.mp4 | 26.4 MB |
| 01__classes.html | 90.2 KB |
| 01_time-series-examples.en.srt | 7.3 KB |
| 11 | 27 bytes |
| 03_naive-bayes-classifiers.mp4 | 26.4 MB |
| 03_selecting-the-number-of-bins-in-a-histogram-a-decision-theoretic-approach_hist.pdf | 116.4 KB |
| 03_connected-components.en.srt | 14.6 KB |
| 12 | 51 bytes |
| 05_hubs-and-authorities.mp4 | 26.2 MB |
| 07_practical-guide-to-controlled-experiments-on-the-web-optional_instructions.html | 1.8 KB |
| 07_module-3-quiz_exam.html | 283.0 KB |
| 13 | 523 bytes |
| 02_distance-measures.mp4 | 26.1 MB |
| 01_assignment-3-submission_instructions.html | 1.0 KB |
| 01__4.2_Topic_Modeling.pdf | 446.6 KB |
| 02_help-us-learn-more-about-you_instructions.html | 1.8 KB |
| 14 | 11 bytes |
| 01_introduction-to-supervised-machine-learning.mp4 | 24.9 MB |
| 01__intro.html | 42.8 KB |
| 08_linear-classifiers-support-vector-machines.en.srt | 15.5 KB |
| 15 | 145 bytes |
| 05_linear-regression-least-squares.mp4 | 23.9 MB |
| 05_neural-networks-made-easy-optional_instructions.html | 1.5 KB |
| 06_play-with-neural-networks-tensorflow-playground-optional_instructions.html | 2.0 KB |
| 01_plotting-weather-patterns_assignment2_rubric.pdf | 75.3 KB |
| 01_post-course-survey_instructions.html | 1.7 KB |
| 08_deep-learning-in-a-nutshell-core-concepts-optional_instructions.html | 1.6 KB |
| 14_rules-of-machine-learning-best-practices-for-ml-engineering-optional_rules_of_ml.pdf | 449.5 KB |
| 09_assisting-pathologists-in-detecting-cancer-with-deep-learning-optional_instructions.html | 1.3 KB |
| 03_matplotlib_matplotlib.html | 42.3 KB |
| 07_logistic-regression.en.srt | 17.1 KB |
| 11_the-treachery-of-leakage-optional_instructions.html | 1.4 KB |
| 01__4.1_Semantic_Text_Similarity.pdf | 414.5 KB |
| 12_leakage-in-data-mining-formulation-detection-and-avoidance-optional_instructions.html | 1.7 KB |
| 13_data-leakage-example-the-icml-2013-whale-challenge-optional_instructions.html | 1.6 KB |
| 14_rules-of-machine-learning-best-practices-for-ml-engineering-optional_instructions.html | 1.6 KB |
| 01__classes.html | 90.2 KB |
| 02_congratulations.en.srt | 1.3 KB |
| 01_assignment-4-submission_instructions.html | 1.0 KB |
| 01__3.1_Text_Classification.pdf | 350.2 KB |
| 01__Diamonds-Were-a-Girls-Best-Friend.jpg | 146.8 KB |
| 06_centrality-examples.en.srt | 13.8 KB |
| 16 | 165 bytes |
| 04_key-concepts-in-machine-learning.mp4 | 23.8 MB |
| 11_module-1-quiz_exam.html | 180.3 KB |
| 04_how-to-use-t-sne-effectively_instructions.html | 1.2 KB |
| 05_how-machines-make-sense-of-big-data-an-introduction-to-clustering-algorithms_instructions.html | 1.3 KB |
| 01_preferential-attachment-model.en.srt | 18.4 KB |
| 17 | 363 bytes |
| 02_basic-nlp-tasks-with-nltk.mp4 | 23.5 MB |
| 01_course-syllabus_instructions.html | 11.4 KB |
| 18 | 10 bytes |
| 04_handling-text-in-python.mp4 | 23.4 MB |
| 01__resources.html | 2.1 KB |
| 01__hist.pdf | 116.4 KB |
| 04_handling-text-in-python.en.srt | 22.6 KB |
| 07_lstm-notebook_instructions.html | 1.2 KB |
| 19 | 5 bytes |
| 03_generative-models-and-lda.mp4 | 23.2 MB |
| 01_graphics-lies-misleading-visuals_BookChapterLIES.pdf | 333.4 KB |
| 02_power-laws-and-rich-get-richer-phenomena-optional_instructions.html | 1.4 KB |
| 01__resources.html | 1.8 KB |
| 01__resources.html | 1.8 KB |
| 01__resources.html | 996 bytes |
| 01__3.6_Learning_Text_Classifiers_in_Python.pdf | 349.0 KB |
| 01__Scikit_Learn_Cheat_Sheet_Python.pdf | 145.7 KB |
| 05_node-and-edge-attributes.en.srt | 12.6 KB |
| 03_help-us-learn-more-about-you_instructions.html | 1.7 KB |
| 04_about-the-professor-christopher-brooks.en.srt | 2.1 KB |
| 01__3.3_Naive_Bayes_Classifier.pdf | 261.5 KB |
| 01__Week2_Basic_Charting.pptx | 238.7 KB |
| 06_regression-evaluation.en.srt | 7.8 KB |
| 06_notice-for-coursera-learners-assignment-submission_instructions.html | 1.6 KB |
| 01__1.3_Regular_Expressions.pdf | 258.5 KB |
| 01__2.2_Basic_NLP_Tasks_with_NLTK.pdf | 230.5 KB |
| 08_dark-horse-analytics-optional_instructions.html | 1.3 KB |
| 06_regular-expressions.en.srt | 20.2 KB |
| 20 | 143 bytes |
| 06_regular-expressions.mp4 | 22.6 MB |
| 01__2.1_Basic_Natural_Language_Processing.pdf | 223.3 KB |
| 01__3.2_Identifying_Features_from_Text.pdf | 215.8 KB |
| 04_k-nearest-neighbors-classification-and-regression.en.srt | 17.1 KB |
| 01__resources.html | 997 bytes |
| 21 | 12 bytes |
| 01_semantic-text-similarity.mp4 | 22.5 MB |
| 02_betweenness-centrality.en.srt | 24.6 KB |
| 22 | 574 bytes |
| 06_bipartite-graphs.mp4 | 22.4 MB |
| 02_becoming-an-independent-data-scientist_assignment4_rubric.pdf | 85.6 KB |
| 01_a-conversation-with-andrew-ng.en.srt | 2.5 KB |
| 23 | 27 bytes |
| 03_advanced-nlp-tasks-with-nltk.mp4 | 21.8 MB |
| 09_module-3-quiz_exam.html | 202.9 KB |
| 04_ten-simple-rules-for-better-figures_instructions.html | 1.5 KB |
| 02_basic-nlp-tasks-with-nltk.en.srt | 20.9 KB |
| 24 | 141 bytes |
| 01_degree-and-closeness-centrality.mp4 | 21.4 MB |
| 11_forecasting-notebook_SP_Week_1_-_Lesson_3_-_Notebook.ipynb | 66.9 KB |
| 07_module-4-quiz_exam.html | 4.9 KB |
| 25 | 57 bytes |
| 06_learning-text-classifiers-in-python.mp4 | 20.3 MB |
| 01__Scikit_Learn_Cheat_Sheet_Python.pdf | 145.7 KB |
| 14_lstm-notebook_SP_Week_3_Lesson_4_-_LSTM.ipynb | 66.9 KB |
| 06_adjusting-the-learning-rate-dynamically.en.srt | 4.3 KB |
| 26 | 9 bytes |
| 08_model-selection-optimizing-classifiers-for-different-evaluation-metrics.mp4 | 20.0 MB |
| 01__Scikit_Learn_Cheat_Sheet_Python.pdf | 145.7 KB |
| 09_assisting-pathologists-in-detecting-cancer-with-deep-learning-optional_assisting-pathologists-in-detecting.html | 142.0 KB |
| 01__Week_1_Principles_of_Information_Visualization.html | 84.9 KB |
| 02_building-a-custom-visualization_assignment3_rubric.pdf | 73.6 KB |
| 01__matplotlib.html | 42.3 KB |
| 03_selecting-the-number-of-bins-in-a-histogram-a-decision-theoretic-approach_instructions.html | 1.2 KB |
| 11_sunspots.en.srt | 2.4 KB |
| 27 | 163 bytes |
| 03_clustering.mp4 | 19.8 MB |
| 01__Week_2_Basic_Charting.html | 73.5 KB |
| 01_course-syllabus_0636920030515.do | 73.2 KB |
| 03_naive-bayes-classifiers.en.srt | 22.6 KB |
| 08_machine-learning-on-time-windows.en.srt | 1.0 KB |
| 28 | 13 bytes |
| 12_the-truthful-art-alberto-cairo.mp4 | 19.5 MB |
| 01__Week_3_Charting_Fundamentals.html | 73.0 KB |
| 02_building-a-custom-visualization_peer_assignment_instructions.html | 1.7 KB |
| 02_graphics-lies-misleading-visuals_assignment1_rubric.pdf | 72.7 KB |
| 09_rnn-notebook_SP_Week_3_Lesson_2_-_RNN.ipynb | 66.9 KB |
| 11_single-layer-neural-network-notebook_SP_Week_2_Lesson_2.ipynb | 66.8 KB |
| 12_sunspots-notebook_SP_Week_4_Lesson_5.ipynb | 66.8 KB |
| 03_spurious-correlations_instructions.html | 1.6 KB |
| 01_becoming-an-independent-data-scientist.en.srt | 2.6 KB |
| 04_preparing-features-and-labels-notebook_SP_Week_2_Lesson_1.ipynb | 66.8 KB |
| 03_keep-learning-with-michigan-online_instructions.html | 34.1 KB |
| 02_becoming-an-independent-data-scientist_peer_assignment_instructions.html | 1.9 KB |
| 03_post-course-survey_instructions.html | 1.5 KB |
| 12_the-truthful-art-alberto-cairo.en.srt | 12.6 KB |
| 29 | 348 bytes |
| 05_tools-for-thinking-about-design-alberto-cairo.mp4 | 19.2 MB |
| 01__resources.html | 1.7 KB |
| 14_deep-neural-network-notebook_SP_Week_2_Lesson_3.ipynb | 66.8 KB |
| 07_lstm-notebook_SP_Week_4_Lesson_1.ipynb | 66.8 KB |
| 12_sunspots-notebook_SP_Week_4_Lesson_3.ipynb | 66.8 KB |
| 05_introduction-to-time-series-notebook_SP_Week_1_Lesson_2.ipynb | 66.8 KB |
| 11_cross-validation.en.srt | 13.0 KB |
| 30 | 237 bytes |
| 10_data-leakage.mp4 | 19.1 MB |
| 02_keep-learning-with-michigan-online_instructions.html | 34.1 KB |
| 02_keep-learning-with-michigan-online_instructions.html | 34.1 KB |
| 05_support-vector-machines.en.srt | 32.0 KB |
| 01__resources.html | 1.8 KB |
| 01__resources.html | 1.3 KB |
| 06_additional-resources-readings_wordnet.html | 31.0 KB |
| 01_model-evaluation-selection.en.srt | 30.1 KB |
| 03_small-world-networks.en.srt | 30.0 KB |
| 12_decision-trees.en.srt | 28.4 KB |
| 02_help-us-learn-more-about-you_instructions.html | 1.9 KB |
| 04_neural-networks.en.srt | 27.9 KB |
| 04_link-prediction.en.srt | 27.7 KB |
| 06_linear-regression-ridge-lasso-and-polynomial-regression.en.srt | 27.2 KB |
| 09_k-nearest-neighbors-classification.en.srt | 26.2 KB |
| 02_distance-measures.en.srt | 26.1 KB |
| 07_interactivity.en.srt | 7.4 KB |
| 31 | 120 bytes |
| 07_an-example-machine-learning-problem.mp4 | 19.1 MB |
| 07_notice-for-auditing-learners-assignment-submission_instructions.html | 1.6 KB |
| 10_kernelized-support-vector-machines.en.srt | 25.6 KB |
| 05_information-extraction.en.srt | 22.5 KB |
| 05_linear-regression-least-squares.en.srt | 21.3 KB |
| 01_assignment-1-submission_instructions.html | 1.1 KB |
| 03_advanced-nlp-tasks-with-nltk.en.srt | 20.1 KB |
| 06_learning-text-classifiers-in-python.en.srt | 19.9 KB |
| 03_clustering.en.srt | 19.9 KB |
| 01_clustering-coefficient.en.srt | 19.4 KB |
| 01__resources.html | 1.8 KB |
| 05_hubs-and-authorities.en.srt | 19.0 KB |
| 04_key-concepts-in-machine-learning.en.srt | 18.8 KB |
| 01_degree-and-closeness-centrality.en.srt | 18.4 KB |
| 03_generative-models-and-lda.en.srt | 18.2 KB |
| 08_model-selection-optimizing-classifiers-for-different-evaluation-metrics.en.srt | 18.1 KB |
| 02_random-forests.en.srt | 17.1 KB |
| 01_assignment-2-submission_instructions.html | 1.0 KB |
| 10_data-leakage.en.srt | 16.7 KB |
| 02_introduction.en.srt | 16.1 KB |
| 02_confusion-matrices-basic-evaluation-metrics.en.srt | 15.8 KB |
| 02_overfitting-and-underfitting.en.srt | 15.8 KB |
| 05_multi-class-evaluation.en.srt | 15.2 KB |
| 01_text-classification.en.srt | 15.2 KB |
| 04_network-robustness.en.srt | 14.9 KB |
| 07_an-example-machine-learning-problem.en.srt | 14.8 KB |
| 04_network-definition-and-vocabulary.en.srt | 14.2 KB |
| 02_identifying-features-from-text.en.srt | 9.6 KB |
| 32 | 276 bytes |
| 04_network-robustness.mp4 | 18.9 MB |
| 03_basic-page-rank.en.srt | 14.1 KB |
| 01_assignment-3-submission_instructions.html | 1.0 KB |
| 04_scaled-page-rank.en.srt | 13.6 KB |
| 09_internationalization-and-issues-with-non-ascii-characters.en.srt | 13.6 KB |
| 02_dimensionality-reduction-and-manifold-learning.en.srt | 13.5 KB |
| 05_tools-for-thinking-about-design-alberto-cairo.en.srt | 12.6 KB |
| 01_course-syllabus_instructions.html | 12.5 KB |
| 07_demonstration-case-study-sentiment-analysis.en.srt | 12.2 KB |
| 10_resources-common-issues-with-free-text_instructions.html | 1.9 KB |
| 33 | 18 bytes |
| 04_scaled-page-rank.mp4 | 18.7 MB |
| 06_the-small-world-phenomenon-optional_instructions.html | 1.6 KB |
| 02_histograms.en.srt | 12.1 KB |
| 08_examining-the-data.en.srt | 12.1 KB |
| 01_assignment-4-submission_instructions.html | 1.0 KB |
| 05_basic-plotting-with-matplotlib.en.srt | 11.9 KB |
| 07_line-plots.en.srt | 11.8 KB |
| 02_syllabus_instructions.html | 11.6 KB |
| 06_scatterplots.en.srt | 11.5 KB |
| 01__documentation.html | 582 bytes |
| 01__resources.html | 2.2 KB |
| 01_course-syllabus_instructions.html | 11.4 KB |
| 01__resources.html | 1.8 KB |
| 02_seaborn.en.srt | 11.3 KB |
| 01_naive-bayes-classifiers.en.srt | 11.2 KB |
| 11_module-1-quiz_exam.html | 10.9 KB |
| 03_networks-definition-and-why-we-study-them.en.srt | 10.8 KB |
| 01_subplots.en.srt | 10.5 KB |
| 08_ta-demonstration-loading-graphs-in-networkx.en.srt | 10.4 KB |
| 07_deep-learning-optional.en.srt | 10.3 KB |
| 04_box-plots.en.srt | 10.3 KB |
| 02_matplotlib-architecture.en.srt | 10.2 KB |
| 02_topic-modeling.en.srt | 10.1 KB |
| 01_plotting-with-pandas.en.srt | 9.5 KB |
| 03_classifier-decision-functions.en.srt | 9.0 KB |
| 12_week-1-quiz_exam.html | 8.9 KB |
| 03_common-patterns-in-time-series.en.srt | 8.8 KB |
| 14_week-4-quiz_exam.html | 8.5 KB |
| 03_gradient-boosted-decision-trees.en.srt | 8.4 KB |
| 15_week-3-quiz_exam.html | 8.4 KB |
| 01__resources.html | 2.9 KB |
| 01_assignment-reading_instructions.html | 1.5 KB |
| 09_multi-class-classification.en.srt | 8.3 KB |
| 34 | 425 bytes |
| 01_clustering-coefficient.mp4 | 18.7 MB |
| 10_forecasting.en.srt | 7.8 KB |
| 08_practice-quiz_quiz.html | 7.8 KB |
| 01__documentation.html | 582 bytes |
| 05_notice-for-auditing-learners-assignment-submission_instructions.html | 1.6 KB |
| 04_precision-recall-and-roc-curves.en.srt | 7.5 KB |
| 10_useful-junk-the-effects-of-visual-embellishment-on-comprehension-and_instructions.html | 1.3 KB |
| 09_graphical-heuristics-chart-junk-edward-tufte.en.srt | 7.6 KB |
| 05_ta-demonstration-simple-network-visualizations-in-networkx.en.srt | 7.3 KB |
| 06_animation.en.srt | 7.1 KB |
| 07_graphical-heuristics-data-ink-ratio-edward-tufte.en.srt | 7.0 KB |
| 04_introduction-to-time-series.en.srt | 6.9 KB |
| 03_supervised-learning-datasets.en.srt | 6.7 KB |
| 01_introduction-a-conversation-with-andrew-ng.en.srt | 6.7 KB |
| 08_module-3-quiz_exam.html | 6.6 KB |
| 01_assignment-1-submission_instructions.html | 1.1 KB |
| 13_combining-our-tools-for-analysis.en.srt | 6.5 KB |
| 01_introduction.en.srt | 6.5 KB |
| 12_deep-neural-network-training-tuning-and-prediction.en.srt | 6.4 KB |
| 02_post-course-survey_instructions.html | 1.5 KB |
| 08_real-data-sunspots.en.srt | 6.4 KB |
| 03_matplotlib_instructions.html | 1.4 KB |
| 04_practice-quiz_quiz.html | 2.2 KB |
| 02_preparing-features-and-labels.en.srt | 6.2 KB |
| 01_assignment-2-submission_instructions.html | 1.0 KB |
| 03_preparing-features-and-labels.en.srt | 6.2 KB |
| 05_python-tools-for-machine-learning.en.srt | 6.1 KB |
| 07_demonstration-regex-with-pandas-and-named-groups.en.srt | 6.1 KB |
| 04_naive-bayes-variations.en.srt | 6.1 KB |
| 01__resources.html | 6.1 KB |
| 04_bi-directional-lstms.en.srt | 6.0 KB |
| 09_dejunkifying-a-plot.en.srt | 5.9 KB |
| 05_heatmaps.en.srt | 5.3 KB |
| 07_single-layer-neural-network.en.srt | 5.2 KB |
| 06_train-validation-and-test-sets.en.srt | 5.2 KB |
| 02_conceptual-overview.en.srt | 5.1 KB |
| 05_module-2-quiz_exam.html | 4.7 KB |
| 08_moving-average-and-differencing.en.srt | 4.5 KB |
| 01_specialization-wrap-up-a-conversation-with-andrew-ng.en.srt | 4.5 KB |
| 13_deep-neural-network.en.srt | 4.5 KB |
| 01_assignment-3-submission_instructions.html | 1.1 KB |
| 01_basic-natural-language-processing.en.srt | 4.2 KB |
| 01_graphics-lies-misleading-visuals_instructions.html | 1.4 KB |
| 09_prediction.en.srt | 4.2 KB |
| 09_train-and-tune-the-model.en.srt | 4.2 KB |
| 03_introduction-to-text-mining.en.srt | 4.1 KB |
| 01_conclusion.en.srt | 3.9 KB |
| 10_more-on-single-layer-neural-network.en.srt | 3.9 KB |
| 12_coding-lstms.en.srt | 3.8 KB |
| 03_shape-of-the-inputs-to-the-rnn.en.srt | 3.5 KB |
| 07_metrics-for-evaluating-performance.en.srt | 3.3 KB |
| 06_feeding-windowed-dataset-into-neural-network.en.srt | 3.3 KB |
| 02_graphics-lies-misleading-visuals_peer_assignment_instructions.html | 3.2 KB |
| 01__resources.html | 3.0 KB |
| 01_assignment-4-submission_instructions.html | 1.0 KB |
| 01_post-course-survey_instructions.html | 1.7 KB |
| 05_lambda-layers.en.srt | 2.9 KB |
| 10_lstm.en.srt | 2.8 KB |
| 13_more-on-lstm.en.srt | 2.8 KB |
| 01__documentation.html | 582 bytes |
| 02_machine-learning-applied-to-time-series.en.srt | 2.8 KB |
| 01__resources.html | 2.3 KB |
| 08_rnn.en.srt | 2.7 KB |
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