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Coursera Machine Learning Specialization by DeepLearning AI DevCourseWeb

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Added Thursday 6th July 2023 07:32:39 PM (3 years ago)
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Torrent Files (470)
FilenameSize
Get Bonus Downloads Here.url182 bytes
Bonus Resources.txt386 bytes
01_welcome.en.srt5.4 KB
01_welcome.en.txt2.8 KB
01_welcome.mp410.6 MB
02_neurons-and-the-brain.en.srt18.3 KB
02_neurons-and-the-brain.en.txt9.5 KB
02_neurons-and-the-brain.mp426.9 MB
03_demand-prediction.en.srt26.6 KB
03_demand-prediction.en.txt14.0 KB
03_demand-prediction.mp424.2 MB
04_example-recognizing-images.en.srt10.2 KB
04_example-recognizing-images.en.txt5.3 KB
04_example-recognizing-images.mp414.6 MB
01_neural-network-layer.en.srt13.0 KB
01_neural-network-layer.en.txt6.8 KB
01_neural-network-layer.mp420.4 MB
02_more-complex-neural-networks.en.srt11.7 KB
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02_more-complex-neural-networks.mp417.0 MB
03_inference-making-predictions-forward-propagation.en.srt7.0 KB
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03_inference-making-predictions-forward-propagation.mp412.6 MB
01_inference-in-code.en.srt10.0 KB
01_inference-in-code.en.txt5.2 KB
01_inference-in-code.mp416.8 MB
02_data-in-tensorflow.en.srt13.2 KB
02_data-in-tensorflow.en.txt8.3 KB
02_data-in-tensorflow.mp424.8 MB
03_building-a-neural-network.en.srt10.7 KB
03_building-a-neural-network.en.txt6.9 KB
03_building-a-neural-network.mp424.4 MB
01_forward-prop-in-a-single-layer.en.srt6.1 KB
01_forward-prop-in-a-single-layer.en.txt3.8 KB
01_forward-prop-in-a-single-layer.mp412.4 MB
02_general-implementation-of-forward-propagation.en.srt11.6 KB
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01_is-there-a-path-to-agi.en.srt16.4 KB
01_is-there-a-path-to-agi.en.txt8.6 KB
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02_matrix-multiplication.en.srt12.3 KB
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03_matrix-multiplication-rules.en.srt11.4 KB
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04_matrix-multiplication-code.en.srt8.8 KB
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01_tensorflow-implementation.en.srt5.9 KB
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01_alternatives-to-the-sigmoid-activation.en.srt6.8 KB
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01_multiclass.en.srt4.3 KB
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02_softmax.en.srt15.4 KB
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04_improved-implementation-of-softmax.en.srt13.4 KB
04_improved-implementation-of-softmax.en.txt7.1 KB
04_improved-implementation-of-softmax.mp415.1 MB
05_classification-with-multiple-outputs-optional.en.srt6.8 KB
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01_advanced-optimization.en.srt10.5 KB
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02_additional-layer-types.en.srt11.3 KB
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01_what-is-a-derivative-optional.en.srt29.7 KB
01_what-is-a-derivative-optional.en.txt15.2 KB
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01_iterative-loop-of-ml-development.en.srt12.1 KB
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02_error-analysis.en.srt13.2 KB
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03_adding-data.en.srt18.9 KB
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05_full-cycle-of-a-machine-learning-project.en.srt14.5 KB
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06_fairness-bias-and-ethics.en.srt13.4 KB
06_fairness-bias-and-ethics.en.txt8.6 KB
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02_trading-off-precision-and-recall.en.txt9.6 KB
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01_decision-tree-model.en.srt10.8 KB
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02_learning-process.en.srt18.0 KB
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01_measuring-purity.en.srt10.2 KB
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02_choosing-a-split-information-gain.en.srt17.4 KB
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02_choosing-a-split-information-gain.mp423.8 MB
03_putting-it-together.en.srt14.6 KB
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03_putting-it-together.mp418.4 MB
04_using-one-hot-encoding-of-categorical-features.en.srt6.6 KB
04_using-one-hot-encoding-of-categorical-features.en.txt4.3 KB
04_using-one-hot-encoding-of-categorical-features.mp414.2 MB
05_continuous-valued-features.en.srt8.6 KB
05_continuous-valued-features.en.txt5.5 KB
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06_regression-trees-optional.en.srt12.2 KB
06_regression-trees-optional.en.txt7.7 KB
06_regression-trees-optional.mp418.9 MB
01_using-multiple-decision-trees.en.srt6.4 KB
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02_sampling-with-replacement.en.srt6.5 KB
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02_sampling-with-replacement.mp414.3 MB
03_random-forest-algorithm.en.srt8.7 KB
03_random-forest-algorithm.en.txt5.6 KB
03_random-forest-algorithm.mp412.7 MB
04_xgboost.en.srt9.4 KB
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05_when-to-use-decision-trees.en.srt10.5 KB
05_when-to-use-decision-trees.en.txt5.6 KB
05_when-to-use-decision-trees.mp417.5 MB
01_andrew-ng-and-chris-manning-on-natural-language-processing.en.srt63.9 KB
01_andrew-ng-and-chris-manning-on-natural-language-processing.en.txt39.9 KB
01_andrew-ng-and-chris-manning-on-natural-language-processing.mp4236.2 MB
01_acknowledgements_instructions.html5.3 KB
01_welcome-to-machine-learning.en.srt3.9 KB
01_welcome-to-machine-learning.en.txt2.4 KB
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02_applications-of-machine-learning.en.srt7.5 KB
02_applications-of-machine-learning.en.txt3.9 KB
02_applications-of-machine-learning.mp433.4 MB
01_what-is-machine-learning.en.srt9.5 KB
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02_supervised-learning-part-1.en.srt10.8 KB
02_supervised-learning-part-1.en.txt5.6 KB
02_supervised-learning-part-1.mp413.9 MB
03_supervised-learning-part-2.en.srt8.9 KB
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04_unsupervised-learning-part-1.en.srt11.6 KB
04_unsupervised-learning-part-1.en.txt7.4 KB
04_unsupervised-learning-part-1.mp418.7 MB
05_unsupervised-learning-part-2.en.srt5.8 KB
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06_jupyter-notebooks.en.srt7.3 KB
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01_linear-regression-model-part-1.en.srt14.8 KB
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01_linear-regression-model-part-1.mp420.3 MB
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04_cost-function-intuition.en.srt20.2 KB
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01_practice-quiz-regression_exam.html2.6 KB
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04_learning-rate.en.srt11.2 KB
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02_tensorflow-implementation-of-collaborative-filtering.mp435.9 MB
03_finding-related-items.en.srt10.2 KB
03_finding-related-items.en.txt5.4 KB
03_finding-related-items.mp416.6 MB
01_collaborative-filtering-vs-content-based-filtering.en.srt14.3 KB
01_collaborative-filtering-vs-content-based-filtering.en.txt7.4 KB
01_collaborative-filtering-vs-content-based-filtering.mp420.0 MB
02_deep-learning-for-content-based-filtering.en.srt14.2 KB
02_deep-learning-for-content-based-filtering.en.txt7.4 KB
02_deep-learning-for-content-based-filtering.mp424.3 MB
03_recommending-from-a-large-catalogue.en.srt10.2 KB
03_recommending-from-a-large-catalogue.en.txt6.4 KB
03_recommending-from-a-large-catalogue.mp418.0 MB
04_ethical-use-of-recommender-systems.en.srt16.9 KB
04_ethical-use-of-recommender-systems.en.txt9.0 KB
04_ethical-use-of-recommender-systems.mp424.8 MB
05_tensorflow-implementation-of-content-based-filtering.en.srt7.3 KB
05_tensorflow-implementation-of-content-based-filtering.en.txt3.9 KB
05_tensorflow-implementation-of-content-based-filtering.mp412.9 MB
01_reducing-the-number-of-features-optional.en.srt18.1 KB
01_reducing-the-number-of-features-optional.en.txt9.4 KB
01_reducing-the-number-of-features-optional.mp426.7 MB
02_pca-algorithm-optional.en.srt24.4 KB
02_pca-algorithm-optional.en.txt12.8 KB
02_pca-algorithm-optional.mp428.0 MB
03_pca-in-code-optional.en.srt16.7 KB
03_pca-in-code-optional.en.txt8.6 KB
03_pca-in-code-optional.mp417.8 MB
01_what-is-reinforcement-learning.en.srt12.5 KB
01_what-is-reinforcement-learning.en.txt8.0 KB
01_what-is-reinforcement-learning.mp431.0 MB
02_mars-rover-example.en.srt10.3 KB
02_mars-rover-example.en.txt5.3 KB
02_mars-rover-example.mp412.7 MB
03_the-return-in-reinforcement-learning.en.srt15.7 KB
03_the-return-in-reinforcement-learning.en.txt8.2 KB
03_the-return-in-reinforcement-learning.mp429.0 MB
04_making-decisions-policies-in-reinforcement-learning.en.srt3.7 KB
04_making-decisions-policies-in-reinforcement-learning.en.txt2.0 KB
04_making-decisions-policies-in-reinforcement-learning.mp45.8 MB
05_review-of-key-concepts.en.srt8.5 KB
05_review-of-key-concepts.en.txt4.5 KB
05_review-of-key-concepts.mp411.4 MB
01_state-action-value-function-definition.en.srt13.5 KB
01_state-action-value-function-definition.en.txt8.3 KB
01_state-action-value-function-definition.mp419.8 MB
02_state-action-value-function-example.en.srt6.8 KB
02_state-action-value-function-example.en.txt4.3 KB
02_state-action-value-function-example.mp414.6 MB
03_bellman-equation.en.srt17.7 KB
03_bellman-equation.en.txt9.2 KB
03_bellman-equation.mp426.7 MB
04_random-stochastic-environment-optional.en.srt13.1 KB
04_random-stochastic-environment-optional.en.txt6.9 KB
04_random-stochastic-environment-optional.mp419.3 MB
01_example-of-continuous-state-space-applications.en.srt9.7 KB
01_example-of-continuous-state-space-applications.en.txt5.0 KB
01_example-of-continuous-state-space-applications.mp427.0 MB
02_lunar-lander.en.srt7.8 KB
02_lunar-lander.en.txt4.9 KB
02_lunar-lander.mp410.4 MB
03_learning-the-state-value-function.en.srt25.2 KB
03_learning-the-state-value-function.en.txt12.9 KB
03_learning-the-state-value-function.mp431.1 MB
04_algorithm-refinement-improved-neural-network-architecture.en.srt4.7 KB
04_algorithm-refinement-improved-neural-network-architecture.en.txt2.5 KB
04_algorithm-refinement-improved-neural-network-architecture.mp47.8 MB
05_algorithm-refinement-greedy-policy.en.srt14.2 KB
05_algorithm-refinement-greedy-policy.en.txt7.5 KB
05_algorithm-refinement-greedy-policy.mp425.3 MB
06_algorithm-refinement-mini-batch-and-soft-updates-optional.en.srt17.7 KB
06_algorithm-refinement-mini-batch-and-soft-updates-optional.en.txt9.4 KB
06_algorithm-refinement-mini-batch-and-soft-updates-optional.mp425.6 MB
07_the-state-of-reinforcement-learning.en.srt4.0 KB
07_the-state-of-reinforcement-learning.en.txt2.6 KB
07_the-state-of-reinforcement-learning.mp47.9 MB
01_summary-and-thank-you.en.srt5.3 KB
01_summary-and-thank-you.en.txt2.8 KB
01_summary-and-thank-you.mp413.9 MB
01_andrew-ng-and-chelsea-finn-on-ai-and-robotics.en.srt50.6 KB
01_andrew-ng-and-chelsea-finn-on-ai-and-robotics.en.txt31.7 KB
01_andrew-ng-and-chelsea-finn-on-ai-and-robotics.mp4230.7 MB
01_acknowledgments_instructions.html5.3 KB
02_optional-opportunity-to-mentor-other-learners_instructions.html1.7 KB
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