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种子名称： Coursera - Machine Learning Specialization
文件类型： 视频
文件数目： 151个文件
文件大小： 3.45 GB
收录时间： 2025-8-7 21:53
已经下载： 3次
资源热度： 30
最近下载： 2025-9-2 09:25

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Coursera - Machine Learning Specialization.torrent

advanced-learning-algorithms/01_neural-networks/01_neural-networks-intuition/01_welcome.mp410.64MB

advanced-learning-algorithms/01_neural-networks/01_neural-networks-intuition/02_neurons-and-the-brain.mp426.86MB

advanced-learning-algorithms/01_neural-networks/01_neural-networks-intuition/03_demand-prediction.mp424.19MB

advanced-learning-algorithms/01_neural-networks/01_neural-networks-intuition/04_example-recognizing-images.mp414.59MB

advanced-learning-algorithms/01_neural-networks/02_neural-network-model/01_neural-network-layer.mp420.43MB

advanced-learning-algorithms/01_neural-networks/02_neural-network-model/02_more-complex-neural-networks.mp417.03MB

advanced-learning-algorithms/01_neural-networks/02_neural-network-model/03_inference-making-predictions-forward-propagation.mp412.55MB

advanced-learning-algorithms/01_neural-networks/03_tensorflow-implementation/01_inference-in-code.mp416.82MB

advanced-learning-algorithms/01_neural-networks/03_tensorflow-implementation/02_data-in-tensorflow.mp424.83MB

advanced-learning-algorithms/01_neural-networks/03_tensorflow-implementation/03_building-a-neural-network.mp424.4MB

advanced-learning-algorithms/01_neural-networks/04_neural-network-implementation-in-python/01_forward-prop-in-a-single-layer.mp412.38MB

advanced-learning-algorithms/01_neural-networks/04_neural-network-implementation-in-python/02_general-implementation-of-forward-propagation.mp421.33MB

advanced-learning-algorithms/01_neural-networks/05_speculations-on-artificial-general-intelligence-agi/01_is-there-a-path-to-agi.mp428.09MB

advanced-learning-algorithms/01_neural-networks/06_vectorization-optional/01_how-neural-networks-are-implemented-efficiently.mp412.24MB

advanced-learning-algorithms/01_neural-networks/06_vectorization-optional/02_matrix-multiplication.mp415.89MB

advanced-learning-algorithms/01_neural-networks/06_vectorization-optional/03_matrix-multiplication-rules.mp416.14MB

advanced-learning-algorithms/01_neural-networks/06_vectorization-optional/04_matrix-multiplication-code.mp413.38MB

advanced-learning-algorithms/02_neural-network-training/01_neural-network-training/01_tensorflow-implementation.mp411.4MB

advanced-learning-algorithms/02_neural-network-training/01_neural-network-training/02_training-details.mp424.08MB

advanced-learning-algorithms/02_neural-network-training/02_activation-functions/01_alternatives-to-the-sigmoid-activation.mp411.96MB

advanced-learning-algorithms/02_neural-network-training/02_activation-functions/02_choosing-activation-functions.mp423.39MB

advanced-learning-algorithms/02_neural-network-training/02_activation-functions/03_why-do-we-need-activation-functions.mp412.93MB

advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/01_multiclass.mp48.37MB

advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/02_softmax.mp420.69MB

advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/03_neural-network-with-softmax-output.mp415.03MB

advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/04_improved-implementation-of-softmax.mp415.05MB

advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/05_classification-with-multiple-outputs-optional.mp411.31MB

advanced-learning-algorithms/02_neural-network-training/04_additional-neural-network-concepts/01_advanced-optimization.mp415.57MB

advanced-learning-algorithms/02_neural-network-training/04_additional-neural-network-concepts/02_additional-layer-types.mp419.52MB

advanced-learning-algorithms/02_neural-network-training/05_back-propagation-optional/01_what-is-a-derivative-optional.mp438.3MB

advanced-learning-algorithms/02_neural-network-training/05_back-propagation-optional/02_computation-graph-optional.mp429.97MB

advanced-learning-algorithms/02_neural-network-training/05_back-propagation-optional/03_larger-neural-network-example-optional.mp426.11MB

advanced-learning-algorithms/03_advice-for-applying-machine-learning/01_advice-for-applying-machine-learning/01_deciding-what-to-try-next.mp411.45MB

advanced-learning-algorithms/03_advice-for-applying-machine-learning/01_advice-for-applying-machine-learning/02_evaluating-a-model.mp419.45MB

advanced-learning-algorithms/03_advice-for-applying-machine-learning/01_advice-for-applying-machine-learning/03_model-selection-and-training-cross-validation-test-sets.mp429.62MB

advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/01_diagnosing-bias-and-variance.mp420.3MB

advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/02_regularization-and-bias-variance.mp421.11MB

advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/03_establishing-a-baseline-level-of-performance.mp419.39MB

advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/04_learning-curves.mp423.28MB

advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/05_deciding-what-to-try-next-revisited.mp428.02MB

advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/06_bias-variance-and-neural-networks.mp426.94MB

advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/01_iterative-loop-of-ml-development.mp414.81MB

advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/02_error-analysis.mp417.51MB

advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/03_adding-data.mp432.94MB

advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/04_transfer-learning-using-data-from-a-different-task.mp419.02MB

advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/05_full-cycle-of-a-machine-learning-project.mp416.35MB

advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/06_fairness-bias-and-ethics.mp425.35MB

advanced-learning-algorithms/03_advice-for-applying-machine-learning/04_skewed-datasets-optional/01_error-metrics-for-skewed-datasets.mp418.95MB

advanced-learning-algorithms/03_advice-for-applying-machine-learning/04_skewed-datasets-optional/02_trading-off-precision-and-recall.mp422.17MB

advanced-learning-algorithms/04_decision-trees/01_decision-trees/01_decision-tree-model.mp414.76MB

advanced-learning-algorithms/04_decision-trees/01_decision-trees/02_learning-process.mp429.03MB

advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/01_measuring-purity.mp415.97MB

advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/02_choosing-a-split-information-gain.mp423.77MB

advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/03_putting-it-together.mp418.41MB

advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/04_using-one-hot-encoding-of-categorical-features.mp414.17MB

advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/05_continuous-valued-features.mp415.89MB

advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/06_regression-trees-optional.mp418.9MB

advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/01_using-multiple-decision-trees.mp412.51MB

advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/02_sampling-with-replacement.mp414.33MB

advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/03_random-forest-algorithm.mp412.72MB

advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/04_xgboost.mp421.08MB

advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/05_when-to-use-decision-trees.mp417.47MB

advanced-learning-algorithms/04_decision-trees/05_conversations-with-andrew-optional/01_andrew-ng-and-chris-manning-on-natural-language-processing.mp4236.15MB

machine-learning/01_week-1-introduction-to-machine-learning/01_overview-of-machine-learning/01_welcome-to-machine-learning.mp422.19MB

machine-learning/01_week-1-introduction-to-machine-learning/01_overview-of-machine-learning/02_applications-of-machine-learning.mp433.45MB

machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/01_what-is-machine-learning.mp425.98MB

machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/02_supervised-learning-part-1.mp413.87MB

machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/03_supervised-learning-part-2.mp414.39MB

machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/04_unsupervised-learning-part-1.mp418.72MB

machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/05_unsupervised-learning-part-2.mp48.25MB

machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/06_jupyter-notebooks.mp419.9MB

machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/01_linear-regression-model-part-1.mp420.27MB

machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/02_linear-regression-model-part-2.mp416.22MB

machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/03_cost-function-formula.mp416.73MB

machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/04_cost-function-intuition.mp429.56MB

machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/05_visualizing-the-cost-function.mp417.32MB

machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/06_visualization-examples.mp417.18MB

machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/01_gradient-descent.mp422.48MB

machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/02_implementing-gradient-descent.mp420.91MB

machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/03_gradient-descent-intuition.mp413.2MB

machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/04_learning-rate.mp416.94MB

machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/05_gradient-descent-for-linear-regression.mp416.38MB

machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/06_running-gradient-descent.mp418.37MB

machine-learning/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/01_multiple-features.mp418.89MB

machine-learning/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/02_vectorization-part-1.mp417.27MB

machine-learning/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/03_vectorization-part-2.mp417.26MB

machine-learning/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/04_gradient-descent-for-multiple-linear-regression.mp419.36MB

machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/01_feature-scaling-part-1.mp413.64MB

machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/02_feature-scaling-part-2.mp414.39MB

machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/03_checking-gradient-descent-for-convergence.mp410.99MB

machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/04_choosing-the-learning-rate.mp416.31MB

machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/05_feature-engineering.mp47.85MB

machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/06_polynomial-regression.mp422.84MB

machine-learning/03_week-3-classification/01_classification-with-logistic-regression/01_motivations.mp420.96MB

machine-learning/03_week-3-classification/01_classification-with-logistic-regression/02_logistic-regression.mp421.48MB

machine-learning/03_week-3-classification/01_classification-with-logistic-regression/03_decision-boundary.mp418.94MB

machine-learning/03_week-3-classification/02_cost-function-for-logistic-regression/01_cost-function-for-logistic-regression.mp424.61MB

machine-learning/03_week-3-classification/02_cost-function-for-logistic-regression/02_simplified-cost-function-for-logistic-regression.mp411.74MB

machine-learning/03_week-3-classification/03_gradient-descent-for-logistic-regression/01_gradient-descent-implementation.mp412.76MB

machine-learning/03_week-3-classification/04_the-problem-of-overfitting/01_the-problem-of-overfitting.mp423.97MB

machine-learning/03_week-3-classification/04_the-problem-of-overfitting/02_addressing-overfitting.mp415.73MB

machine-learning/03_week-3-classification/04_the-problem-of-overfitting/03_cost-function-with-regularization.mp417.1MB

machine-learning/03_week-3-classification/04_the-problem-of-overfitting/04_regularized-linear-regression.mp419.81MB

machine-learning/03_week-3-classification/04_the-problem-of-overfitting/05_regularized-logistic-regression.mp420.9MB

machine-learning/03_week-3-classification/06_conversations-with-andrew-optional/01_andrew-ng-and-fei-fei-li-on-human-centered-ai.mp4214.72MB

unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/01_welcome-to-the-course/01_welcome.mp48.27MB

unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/01_what-is-clustering.mp48.82MB

unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/02_k-means-intuition.mp412.36MB

unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/03_k-means-algorithm.mp419.76MB

unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/04_optimization-objective.mp429.51MB

unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/05_initializing-k-means.mp417.84MB

unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/06_choosing-the-number-of-clusters.mp416.85MB

unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/01_finding-unusual-events.mp426.28MB

unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/02_gaussian-normal-distribution.mp420.88MB

unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/03_anomaly-detection-algorithm.mp420.32MB

unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/04_developing-and-evaluating-an-anomaly-detection-system.mp423.9MB

unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/05_anomaly-detection-vs-supervised-learning.mp420.31MB

unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/06_choosing-what-features-to-use.mp430.87MB

unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/01_collaborative-filtering/01_making-recommendations.mp420.44MB

unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/01_collaborative-filtering/02_using-per-item-features.mp423.49MB

unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/01_collaborative-filtering/03_collaborative-filtering-algorithm.mp431.03MB

unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/01_collaborative-filtering/04_binary-labels-favs-likes-and-clicks.mp419.84MB

unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/02_recommender-systems-implementation-detail/01_mean-normalization.mp418.9MB

unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/02_recommender-systems-implementation-detail/02_tensorflow-implementation-of-collaborative-filtering.mp435.87MB

unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/02_recommender-systems-implementation-detail/03_finding-related-items.mp416.62MB

unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/01_collaborative-filtering-vs-content-based-filtering.mp419.97MB

unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/02_deep-learning-for-content-based-filtering.mp424.34MB

unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/03_recommending-from-a-large-catalogue.mp417.98MB

unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/04_ethical-use-of-recommender-systems.mp424.83MB

unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/05_tensorflow-implementation-of-content-based-filtering.mp412.94MB

unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/04_principal-component-analysis/01_reducing-the-number-of-features-optional.mp426.7MB

unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/04_principal-component-analysis/02_pca-algorithm-optional.mp428.01MB

unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/04_principal-component-analysis/03_pca-in-code-optional.mp417.8MB

unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/01_what-is-reinforcement-learning.mp430.97MB

unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/02_mars-rover-example.mp412.65MB

unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/03_the-return-in-reinforcement-learning.mp429.01MB

unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/04_making-decisions-policies-in-reinforcement-learning.mp45.81MB

unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/05_review-of-key-concepts.mp411.39MB

unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/02_state-action-value-function/01_state-action-value-function-definition.mp419.84MB

unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/02_state-action-value-function/02_state-action-value-function-example.mp414.64MB

unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/02_state-action-value-function/03_bellman-equation.mp426.66MB

unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/02_state-action-value-function/04_random-stochastic-environment-optional.mp419.27MB

unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/01_example-of-continuous-state-space-applications.mp427.05MB

unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/02_lunar-lander.mp410.37MB

unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/03_learning-the-state-value-function.mp431.14MB

unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/04_algorithm-refinement-improved-neural-network-architecture.mp47.79MB

unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/05_algorithm-refinement-greedy-policy.mp425.27MB

unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/06_algorithm-refinement-mini-batch-and-soft-updates-optional.mp425.55MB

unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/07_the-state-of-reinforcement-learning.mp47.86MB

unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/05_summary-and-thank-you/01_summary-and-thank-you.mp413.94MB

unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/06_conversations-with-andrew-optional/01_andrew-ng-and-chelsea-finn-on-ai-and-robotics.mp4230.66MB