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Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/03_state-action-value-function/03_bellman-equations.mp4 28.0 MBCoursera -/03_advice-for-applying-machine-learning/04_skewed-datasets-optional/02_trading-off-precision-and-recall.mp4 27.9 MBCoursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/04_anomaly-detection/01_finding-unusual-events.mp4 27.0 MBCoursera -/03_advice-for-applying-machine-learning/03_machine-learning-development-process/06_fairness-bias-and-ethics.mp4 26.6 MBCoursera -/03_advice-for-applying-machine-learning/02_bias-and-variance/02_regularization-and-bias-variance.mp4 26.4 MBCoursera -/01_neural-networks/03_tensorflow-implementation/02_data-in-tensorflow.mp4 26.1 MBCoursera -/02_neural-network-training/01_neural-network-training/02_training-details.mp4 25.8 MBCoursera -/01_neural-networks/03_tensorflow-implementation/03_building-a-neural-network.mp4 25.5 MBCoursera -/03_advice-for-applying-machine-learning/02_bias-and-variance/01_diagnosing-bias-and-variance.mp4 25.3 MBCoursera -/03_advice-for-applying-machine-learning/03_machine-learning-development-process/04_transfer-learning-using-data-from-a-different-task.mp4 24.9 MBCoursera - Unsupervised Learning, Recommenders, Reinforcement Learning/02_recommender-systems/01_collaborative-filtering/02_using-per-item-features.mp4 24.8 MBCoursera -/03_advice-for-applying-machine-learning/01_advice-for-applying-machine-learning/02_evaluating-a-model.mp4 24.8 MBCoursera -/02_neural-network-training/02_activation-functions/02_choosing-activation-functions.mp4 24.5 MBCoursera -/04_decision-trees/02_decision-tree-learning/02_choosing-a-split-information-gain.mp4 24.4 MBCoursera -/04_decision-trees/03_tree-ensembles/04_xgboost.mp4 23.8 MBCoursera -/03_advice-for-applying-machine-learning/04_skewed-datasets-optional/01_error-metrics-for-skewed-datasets.mp4 23.7 MBCoursera -/02_neural-network-training/04_additional-neural-network-concepts/02_additional-layer-types.mp4 23.2 MBCoursera -/03_advice-for-applying-machine-learning/02_bias-and-variance/03_establishing-a-baseline-level-of-performance.mp4 22.9 MBCoursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/04_anomaly-detection/03_anomaly-detection-algorithm.mp4 22.6 MBCoursera - Supervised Machine Learning Regression and Classification/03_week-3-classification/01_classification-with-logistic-regression/01_motivations.mp4 22.0 MBCoursera -/02_neural-network-training/03_multiclass-classification/02_softmax.mp4 21.7 MBCoursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/04_anomaly-detection/02_gaussian-normal-distribution.mp4 21.6 MBCoursera - Unsupervised Learning, Recommenders, Reinforcement Learning/02_recommender-systems/01_collaborative-filtering/01_making-recommendations.mp4 21.4 MBCoursera -/01_neural-networks/02_neural-network-model/01_neural-network-layer.mp4 21.4 MBCoursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/02_clustering/03_k-means-algorithm.mp4 20.7 MBCoursera -/01_neural-networks/04_neural-network-implementation-in-python/02_general-implementation-of-forward-propagation.mp4 20.7 MBCoursera -/04_decision-trees/03_tree-ensembles/05_when-to-use-decision-trees.mp4 20.3 MBCoursera -/04_decision-trees/02_decision-tree-learning/03_putting-it-together.mp4 20.3 MBCoursera -/04_decision-trees/02_decision-tree-learning/01_measuring-purity.mp4 19.9 MBCoursera -/04_decision-trees/02_decision-tree-learning/06_regression-trees-optional.mp4 19.8 MBCoursera -/01_neural-networks/06_vectorization-optional/03_matrix-multiplication-rules.mp4 19.4 MBCoursera -/02_neural-network-training/03_multiclass-classification/04_improved-implementation-of-softmax.mp4 18.8 MBCoursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/02_clustering/06_choosing-the-number-of-clusters.mp4 18.8 MBCoursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/02_clustering/05_initializing-k-means.mp4 18.7 MBCoursera -/01_neural-networks/03_tensorflow-implementation/01_inference-in-code.mp4 18.4 MBCoursera -/03_advice-for-applying-machine-learning/03_machine-learning-development-process/02_error-analysis.mp4 18.4 MBCoursera -/03_advice-for-applying-machine-learning/03_machine-learning-development-process/05_full-cycle-of-a-machine-learning-project.mp4 17.1 MBCoursera -/04_decision-trees/02_decision-tree-learning/05_continuous-valued-features.mp4 16.7 MBCoursera -/01_neural-networks/06_vectorization-optional/02_matrix-multiplication.mp4 16.6 MBCoursera - Supervised Machine Learning Regression and Classification/03_week-3-classification/04_the-problem-of-overfitting/02_addressing-overfitting.mp4 16.5 MBCoursera -/01_neural-networks/02_neural-network-model/02_more-complex-neural-networks.mp4 16.4 MBCoursera -/02_neural-network-training/04_additional-neural-network-concepts/01_advanced-optimization.mp4 16.1 MBCoursera -/04_decision-trees/03_tree-ensembles/03_random-forest-algorithm.mp4 16.1 MBCoursera -/02_neural-network-training/03_multiclass-classification/03_neural-network-with-softmax-output.mp4 15.8 MBCoursera -/03_advice-for-applying-machine-learning/03_machine-learning-development-process/01_iterative-loop-of-ml-development.mp4 15.5 MBCoursera -/04_decision-trees/01_decision-trees/01_decision-tree-model.mp4 15.4 MBCoursera -/01_neural-networks/01_neural-networks-intuition/04_example-recognizing-images.mp4 15.2 MBCoursera -/04_decision-trees/03_tree-ensembles/02_sampling-with-replacement.mp4 15.0 MBCoursera -/04_decision-trees/02_decision-tree-learning/04_using-one-hot-encoding-of-categorical-features.mp4 14.9 MBCoursera - Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/07_summary-and-thank-you/01_summary-and-thank-you.mp4 14.6 MBCoursera -/01_neural-networks/06_vectorization-optional/04_matrix-multiplication-code.mp4 14.5 MBCoursera -/01_neural-networks/06_vectorization-optional/01_how-neural-networks-are-implemented-efficiently.mp4 14.5 MBCoursera -/03_advice-for-applying-machine-learning/01_advice-for-applying-machine-learning/01_deciding-what-to-try-next.mp4 13.5 MBCoursera -/02_neural-network-training/02_activation-functions/03_why-do-we-need-activation-functions.mp4 13.5 MBCoursera -/02_neural-network-training/03_multiclass-classification/05_classification-with-multiple-outputs-optional.mp4 13.5 MBCoursera -/01_neural-networks/02_neural-network-model/03_inference-making-predictions-forward-propagation.mp4 13.2 MBCoursera -/04_decision-trees/03_tree-ensembles/01_using-multiple-decision-trees.mp4 13.1 MBCoursera -/01_neural-networks/04_neural-network-implementation-in-python/01_forward-prop-in-a-single-layer.mp4 13.0 MBCoursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/02_clustering/02_k-means-intuition.mp4 13.0 MBCoursera -/02_neural-network-training/02_activation-functions/01_alternatives-to-the-sigmoid-activation.mp4 12.5 MBCoursera -/02_neural-network-training/01_neural-network-training/01_tensorflow-implementation.mp4 12.0 MBCoursera -/01_neural-networks/01_neural-networks-intuition/01_welcome.mp4 11.2 MBCoursera - Unsupervised Learning, Recommenders, Reinforcement Learning/03_reinforcement-learning/05_continuous-state-spaces/02_lunar-lander.mp4 10.6 MBCoursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/02_clustering/01_what-is-clustering.mp4 9.2 MBCoursera - Unsupervised Learning, Recommenders, Reinforcement Learning/01_unsupervised-learning/01_welcome-to-the-course/01_welcome.mp4 8.9 MBCoursera -/02_neural-network-training/03_multiclass-classification/01_multiclass.mp4 8.8 MB
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