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[CourseClub.Me] Coursera – Machine Learning Specialization (Andrew Ng)

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种子名称： [CourseClub.Me] Coursera – Machine Learning Specialization (Andrew Ng)
文件类型： 视频
文件数目： 136个文件
文件大小： 1.47 GB
收录时间： 2023-3-13 21:43
已经下载： 3次
资源热度： 154
最近下载： 2024-5-28 06:27

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CourseClub Me Coursera – Machine Learning Specialization Andrew Ng

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[CourseClub.Me] Coursera – Machine Learning Specialization (Andrew Ng).torrent
  • Coursera - Supervised Machine Learning Regression and Classification/01_week-1-introduction-to-machine-learning/01_overview-of-machine-learning/01_welcome-to-machine-learning.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/01_week-1-introduction-to-machine-learning/01_overview-of-machine-learning/02_applications-of-machine-learning.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/01_week-1-introduction-to-machine-learning/03_regression-model/01_linear-regression-model-part-1.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/01_week-1-introduction-to-machine-learning/03_regression-model/02_linear-regression-model-part-2.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/01_week-1-introduction-to-machine-learning/03_regression-model/03_cost-function-formula.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/01_week-1-introduction-to-machine-learning/03_regression-model/04_cost-function-intuition.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/01_week-1-introduction-to-machine-learning/03_regression-model/05_visualizing-the-cost-function.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/01_week-1-introduction-to-machine-learning/03_regression-model/06_visualization-examples.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/01_gradient-descent.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/02_implementing-gradient-descent.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/03_gradient-descent-intuition.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/04_learning-rate.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/05_gradient-descent-for-linear-regression.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/06_running-gradient-descent.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/01_multiple-features.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/02_vectorization-part-1.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/03_vectorization-part-2.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/04_gradient-descent-for-multiple-linear-regression.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/01_feature-scaling-part-1.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/02_feature-scaling-part-2.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/03_checking-gradient-descent-for-convergence.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/04_choosing-the-learning-rate.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/05_feature-engineering.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/06_polynomial-regression.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/03_week-3-classification/01_classification-with-logistic-regression/01_motivations.mp420.96MB
  • Coursera - Supervised Machine Learning Regression and Classification/03_week-3-classification/01_classification-with-logistic-regression/02_logistic-regression.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/03_week-3-classification/01_classification-with-logistic-regression/03_decision-boundary.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/03_week-3-classification/02_cost-function-for-logistic-regression/01_cost-function-for-logistic-regression.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/03_week-3-classification/02_cost-function-for-logistic-regression/02_simplified-cost-function-for-logistic-regression.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/03_week-3-classification/03_gradient-descent-for-logistic-regression/01_gradient-descent-implementation.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/03_week-3-classification/04_the-problem-of-overfitting/01_the-problem-of-overfitting.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/03_week-3-classification/04_the-problem-of-overfitting/02_addressing-overfitting.mp415.73MB
  • Coursera - Supervised Machine Learning Regression and Classification/03_week-3-classification/04_the-problem-of-overfitting/03_cost-function-with-regularization.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/03_week-3-classification/04_the-problem-of-overfitting/04_regularized-linear-regression.mp40B
  • Coursera - Supervised Machine Learning Regression and Classification/03_week-3-classification/04_the-problem-of-overfitting/05_regularized-logistic-regression.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/01_welcome-to-the-course/01_welcome.mp48.48MB
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/02_clustering/01_what-is-clustering.mp48.82MB
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/02_clustering/02_k-means-intuition.mp412.36MB
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/02_clustering/03_k-means-algorithm.mp419.76MB
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/02_clustering/04_optimization-objective.mp429.51MB
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/02_clustering/05_initializing-k-means.mp417.84MB
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/02_clustering/06_choosing-the-number-of-clusters.mp417.89MB
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/04_anomaly-detection/01_finding-unusual-events.mp425.71MB
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/04_anomaly-detection/02_gaussian-normal-distribution.mp420.6MB
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/04_anomaly-detection/03_anomaly-detection-algorithm.mp421.53MB
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/04_anomaly-detection/04_developing-and-evaluating-an-anomaly-detection-system.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/04_anomaly-detection/05_anomaly-detection-vs-supervised-learning.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/04_anomaly-detection/06_choosing-what-features-to-use.mp431.93MB
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/02_recommender-systems/01_collaborative-filtering/01_making-recommendations.mp420.44MB
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/02_recommender-systems/01_collaborative-filtering/02_using-per-item-features.mp423.69MB
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/02_recommender-systems/01_collaborative-filtering/03_collaborative-filtering-algorithm.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/02_recommender-systems/01_collaborative-filtering/04_binary-labels-favs-likes-and-clicks.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/02_recommender-systems/03_recommender-systems-implementation-detail/01_mean-normalization.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/02_recommender-systems/03_recommender-systems-implementation-detail/02_tensorflow-implementation-of-collaborative-filtering.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/02_recommender-systems/03_recommender-systems-implementation-detail/03_finding-related-items.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/02_recommender-systems/05_content-based-filtering/01_collaborative-filtering-vs-content-based-filtering.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/02_recommender-systems/05_content-based-filtering/02_deep-learning-for-content-based-filtering.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/02_recommender-systems/05_content-based-filtering/03_recommending-from-a-large-catalogue.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/02_recommender-systems/05_content-based-filtering/04_ethical-use-of-recommender-systems.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/02_recommender-systems/05_content-based-filtering/05_tensorflow-implementation-of-content-based-filtering.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/01_reinforcement-learning-introduction/01_what-is-reinforcement-learning.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/01_reinforcement-learning-introduction/02_mars-rover-example.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/01_reinforcement-learning-introduction/03_the-return-in-reinforcement-learning.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/01_reinforcement-learning-introduction/04_making-decisions-policies-in-reinforcement-learning.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/01_reinforcement-learning-introduction/05_review-of-key-concepts.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/03_state-action-value-function/01_state-action-value-function-definition.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/03_state-action-value-function/02_state-action-value-function-example.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/03_state-action-value-function/03_bellman-equations.mp426.66MB
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/03_state-action-value-function/04_random-stochastic-environment-optional.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/05_continuous-state-spaces/01_example-of-continuous-state-space-applications.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/05_continuous-state-spaces/02_lunar-lander.mp410.1MB
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/05_continuous-state-spaces/03_learning-the-state-value-function.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/05_continuous-state-spaces/04_algorithm-refinement-improved-neural-network-architecture.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/05_continuous-state-spaces/05_algorithm-refinement-greedy-policy.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/05_continuous-state-spaces/06_algorithm-refinement-mini-batch-and-soft-updates-optional.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/05_continuous-state-spaces/07_the-state-of-reinforcement-learning.mp40B
  • Coursera - Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/07_summary-and-thank-you/01_summary-and-thank-you.mp413.94MB
  • Coursera -/01_neural-networks/01_neural-networks-intuition/01_welcome.mp410.64MB
  • Coursera -/01_neural-networks/01_neural-networks-intuition/02_neurons-and-the-brain.mp426.86MB
  • Coursera -/01_neural-networks/01_neural-networks-intuition/03_demand-prediction.mp429.48MB
  • Coursera -/01_neural-networks/01_neural-networks-intuition/04_example-recognizing-images.mp414.49MB
  • Coursera -/01_neural-networks/02_neural-network-model/01_neural-network-layer.mp420.44MB
  • Coursera -/01_neural-networks/02_neural-network-model/02_more-complex-neural-networks.mp415.64MB
  • Coursera -/01_neural-networks/02_neural-network-model/03_inference-making-predictions-forward-propagation.mp412.55MB
  • Coursera -/01_neural-networks/03_tensorflow-implementation/01_inference-in-code.mp417.51MB
  • Coursera -/01_neural-networks/03_tensorflow-implementation/02_data-in-tensorflow.mp424.92MB
  • Coursera -/01_neural-networks/03_tensorflow-implementation/03_building-a-neural-network.mp424.34MB
  • Coursera -/01_neural-networks/04_neural-network-implementation-in-python/01_forward-prop-in-a-single-layer.mp412.4MB
  • Coursera -/01_neural-networks/04_neural-network-implementation-in-python/02_general-implementation-of-forward-propagation.mp419.75MB
  • Coursera -/01_neural-networks/05_speculations-on-artificial-general-intelligence-agi/01_is-there-a-path-to-agi.mp428.09MB
  • Coursera -/01_neural-networks/06_vectorization-optional/01_how-neural-networks-are-implemented-efficiently.mp413.79MB
  • Coursera -/01_neural-networks/06_vectorization-optional/02_matrix-multiplication.mp415.85MB
  • Coursera -/01_neural-networks/06_vectorization-optional/03_matrix-multiplication-rules.mp418.46MB
  • Coursera -/01_neural-networks/06_vectorization-optional/04_matrix-multiplication-code.mp413.84MB
  • Coursera -/02_neural-network-training/01_neural-network-training/01_tensorflow-implementation.mp411.48MB
  • Coursera -/02_neural-network-training/01_neural-network-training/02_training-details.mp424.58MB
  • Coursera -/02_neural-network-training/02_activation-functions/01_alternatives-to-the-sigmoid-activation.mp411.96MB
  • Coursera -/02_neural-network-training/02_activation-functions/02_choosing-activation-functions.mp423.39MB
  • Coursera -/02_neural-network-training/02_activation-functions/03_why-do-we-need-activation-functions.mp412.88MB
  • Coursera -/02_neural-network-training/03_multiclass-classification/01_multiclass.mp48.37MB
  • Coursera -/02_neural-network-training/03_multiclass-classification/02_softmax.mp420.68MB
  • Coursera -/02_neural-network-training/03_multiclass-classification/03_neural-network-with-softmax-output.mp415.02MB
  • Coursera -/02_neural-network-training/03_multiclass-classification/04_improved-implementation-of-softmax.mp417.92MB
  • Coursera -/02_neural-network-training/03_multiclass-classification/05_classification-with-multiple-outputs-optional.mp412.87MB
  • Coursera -/02_neural-network-training/04_additional-neural-network-concepts/01_advanced-optimization.mp415.35MB
  • Coursera -/02_neural-network-training/04_additional-neural-network-concepts/02_additional-layer-types.mp422.09MB
  • Coursera -/03_advice-for-applying-machine-learning/01_advice-for-applying-machine-learning/01_deciding-what-to-try-next.mp412.91MB
  • Coursera -/03_advice-for-applying-machine-learning/01_advice-for-applying-machine-learning/02_evaluating-a-model.mp423.62MB
  • Coursera -/03_advice-for-applying-machine-learning/01_advice-for-applying-machine-learning/03_model-selection-and-training-cross-validation-test-sets.mp432.61MB
  • Coursera -/03_advice-for-applying-machine-learning/02_bias-and-variance/01_diagnosing-bias-and-variance.mp424.13MB
  • Coursera -/03_advice-for-applying-machine-learning/02_bias-and-variance/02_regularization-and-bias-variance.mp425.22MB
  • Coursera -/03_advice-for-applying-machine-learning/02_bias-and-variance/03_establishing-a-baseline-level-of-performance.mp421.86MB
  • Coursera -/03_advice-for-applying-machine-learning/02_bias-and-variance/04_learning-curves.mp428.07MB
  • Coursera -/03_advice-for-applying-machine-learning/02_bias-and-variance/05_deciding-what-to-try-next-revisited.mp428.02MB
  • Coursera -/03_advice-for-applying-machine-learning/02_bias-and-variance/06_bias-variance-and-neural-networks.mp426.94MB
  • Coursera -/03_advice-for-applying-machine-learning/03_machine-learning-development-process/01_iterative-loop-of-ml-development.mp414.81MB
  • Coursera -/03_advice-for-applying-machine-learning/03_machine-learning-development-process/02_error-analysis.mp417.51MB
  • Coursera -/03_advice-for-applying-machine-learning/03_machine-learning-development-process/03_adding-data.mp432.71MB
  • Coursera -/03_advice-for-applying-machine-learning/03_machine-learning-development-process/04_transfer-learning-using-data-from-a-different-task.mp423.75MB
  • Coursera -/03_advice-for-applying-machine-learning/03_machine-learning-development-process/05_full-cycle-of-a-machine-learning-project.mp416.35MB
  • Coursera -/03_advice-for-applying-machine-learning/03_machine-learning-development-process/06_fairness-bias-and-ethics.mp425.35MB
  • Coursera -/03_advice-for-applying-machine-learning/04_skewed-datasets-optional/01_error-metrics-for-skewed-datasets.mp422.63MB
  • Coursera -/03_advice-for-applying-machine-learning/04_skewed-datasets-optional/02_trading-off-precision-and-recall.mp426.58MB
  • Coursera -/04_decision-trees/01_decision-trees/01_decision-tree-model.mp414.71MB
  • Coursera -/04_decision-trees/01_decision-trees/02_learning-process.mp429.03MB
  • Coursera -/04_decision-trees/02_decision-tree-learning/01_measuring-purity.mp419.02MB
  • Coursera -/04_decision-trees/02_decision-tree-learning/02_choosing-a-split-information-gain.mp423.26MB
  • Coursera -/04_decision-trees/02_decision-tree-learning/03_putting-it-together.mp419.37MB
  • Coursera -/04_decision-trees/02_decision-tree-learning/04_using-one-hot-encoding-of-categorical-features.mp414.17MB
  • Coursera -/04_decision-trees/02_decision-tree-learning/05_continuous-valued-features.mp415.89MB
  • Coursera -/04_decision-trees/02_decision-tree-learning/06_regression-trees-optional.mp418.9MB
  • Coursera -/04_decision-trees/03_tree-ensembles/01_using-multiple-decision-trees.mp412.51MB
  • Coursera -/04_decision-trees/03_tree-ensembles/02_sampling-with-replacement.mp414.33MB
  • Coursera -/04_decision-trees/03_tree-ensembles/03_random-forest-algorithm.mp415.31MB
  • Coursera -/04_decision-trees/03_tree-ensembles/04_xgboost.mp422.74MB
  • Coursera -/04_decision-trees/03_tree-ensembles/05_when-to-use-decision-trees.mp419.4MB



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