[CourserHub.com] Coursera - Machine Learning Algorithms in the Real World Specialization

Creation Time	April 17, 2025, 1:53 p.m.
Last Access Time	April 25, 2025, 5:33 p.m.
File Size	2.8 GB
Keywords	Real Specialization - Coursera Machine Algorithms Learning in World the com CourserHub
Total Requests	15
Total Files	465
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data-machine-learning/01_what-does-good-data-look-like/01_know-your-problem/03_business-understanding-and-problem-discovery.mp4 49.0 MB
machine-learning-applied/01_introduction-to-machine-learning-applications/01_lesson-1-definitions/04_what-is-artificial-intelligence-and-machine-learning.mp4 43.9 MB
data-machine-learning/01_what-does-good-data-look-like/02_know-your-data/01_data-acquisition-and-understanding.mp4 42.0 MB
data-machine-learning/02_preparing-your-data-for-machine-learning-success/01_consolidate-sources/01_data-warehousing.mp4 40.3 MB
data-machine-learning/01_what-does-good-data-look-like/02_know-your-data/04_features-and-transformations-of-raw-data.mp4 39.1 MB
machine-learning-applied/02_machine-learning-in-the-real-world/01_lesson-1-machines-are-different-from-humans/02_features-and-transformations-of-raw-data.mp4 39.1 MB
data-machine-learning/04_bad-data/01_accept-limitations/02_generalization-and-how-machines-actually-learn.mp4 37.5 MB
machine-learning-applied/02_machine-learning-in-the-real-world/01_lesson-1-machines-are-different-from-humans/01_generalization-and-how-machines-actually-learn.mp4 37.5 MB
machine-learning-classification-algorithms/01_classification-using-decision-trees-and-k-nn/03_k-nearest-neighbours/02_distance-measures.mp4 36.7 MB
data-machine-learning/03_feature-engineering-for-more-fun-profit/03_transfer-learning/01_transfer-learning.mp4 36.7 MB
machine-learning-applied/01_introduction-to-machine-learning-applications/03_lesson-3-broader-machine-learning/03_reinforcement-learning.mp4 33.3 MB
machine-learning-classification-algorithms/01_classification-using-decision-trees-and-k-nn/03_k-nearest-neighbours/01_classification-using-k-nearest-neighbours.mp4 33.1 MB
data-machine-learning/03_feature-engineering-for-more-fun-profit/01_understanding-features/01_what-are-the-simplest-features-to-try.mp4 33.1 MB
data-machine-learning/04_bad-data/03_consequences-of-bad-data/02_live-data-danger.mp4 33.0 MB
machine-learning-classification-algorithms/03_regression-for-classification-support-vector-machines/01_models-with-transfer-functions/02_neural-networks.mp4 32.7 MB
machine-learning-applied/01_introduction-to-machine-learning-applications/01_lesson-1-definitions/06_the-machine-learning-process.mp4 32.2 MB
data-machine-learning/02_preparing-your-data-for-machine-learning-success/02_coordinate/01_everything-has-to-be-numbers.mp4 31.8 MB
data-machine-learning/01_what-does-good-data-look-like/01_know-your-problem/05_exploring-the-process-of-problem-definition.mp4 31.5 MB
machine-learning-applied/04_machine-learning-projects/02_lesson-2-getting-ready-to-model/01_exploring-the-process-of-problem-definition.mp4 31.5 MB
data-machine-learning/04_bad-data/02_statistical-nuance/02_skewed-distributions.mp4 31.2 MB
optimize-machine-learning-model-performance/04_care-and-feeding-of-your-machine-learning-system/01_mapping-the-model-lifecycle/02_post-deployment-challenges.mp4 29.6 MB
data-machine-learning/03_feature-engineering-for-more-fun-profit/02_building-good-features/02_feature-selection.mp4 29.6 MB
machine-learning-classification-algorithms/01_classification-using-decision-trees-and-k-nn/02_decision-trees/02_generalization-and-overfitting.mp4 29.5 MB
machine-learning-applied/01_introduction-to-machine-learning-applications/01_lesson-1-definitions/05_what-about-data-science.mp4 29.3 MB
machine-learning-applied/04_machine-learning-projects/02_lesson-2-getting-ready-to-model/02_assessing-your-quam-for-use-in-your-business.mp4 29.2 MB
optimize-machine-learning-model-performance/02_responsible-machine-learning/01_feedback-fairness/02_positive-feedback-loops-negative-feedback-loops.mp4 28.8 MB
machine-learning-applied/03_learning-data/03_lesson-3-data-process/03_why-you-need-to-set-up-a-data-pipeline.mp4 26.8 MB
machine-learning-classification-algorithms/03_regression-for-classification-support-vector-machines/02_support-vector-machines/02_basics-of-support-vector-machines.mp4 26.6 MB
optimize-machine-learning-model-performance/03_machine-learning-in-production-planning/02_deployment-issues-operational-processes/02_logging-ml-model-versioning.mp4 26.0 MB
machine-learning-classification-algorithms/04_contrasting-models/02_testing-and-validation-procedures/01_testing-your-models.mp4 25.0 MB
data-machine-learning/01_what-does-good-data-look-like/03_matchmaking/02_case-study-problem-from-data.mp4 25.0 MB
machine-learning-classification-algorithms/02_functions-for-fun-and-profit/01_finding-lines/04_gradient-descent.mp4 24.8 MB
optimize-machine-learning-model-performance/02_responsible-machine-learning/02_you-are-what-you-optimize-design-considerations/01_metric-design-observing-behaviours.mp4 24.8 MB
machine-learning-classification-algorithms/03_regression-for-classification-support-vector-machines/03_infinite-feature-expansions/01_kernels.mp4 24.7 MB
machine-learning-applied/03_learning-data/02_lesson-2-data-relates-to-problems/05_noise-and-sources-of-randomness.mp4 24.2 MB
data-machine-learning/04_bad-data/01_accept-limitations/04_bias-and-variance-tradeoff.mp4 24.2 MB
machine-learning-classification-algorithms/02_functions-for-fun-and-profit/02_simple-vs-expressive/02_bias-and-variance-tradeoff.mp4 24.2 MB
machine-learning-applied/04_machine-learning-projects/03_lesson-3-model-learning-and-evaluation/01_technically-assessing-the-strength-of-your-quam.mp4 24.1 MB
optimize-machine-learning-model-performance/01_machine-learning-strategy/03_teamwork-communication/02_understanding-and-communicating-change.mp4 23.7 MB
machine-learning-classification-algorithms/02_functions-for-fun-and-profit/03_from-regression-to-classification/01_loss-for-classification.mp4 23.6 MB
data-machine-learning/02_preparing-your-data-for-machine-learning-success/03_clean-complete/02_data-transformations.mp4 23.6 MB
data-machine-learning/01_what-does-good-data-look-like/03_matchmaking/04_weekly-summary-what-does-good-data-look-like.mp4 23.3 MB
machine-learning-classification-algorithms/02_functions-for-fun-and-profit/02_simple-vs-expressive/01_nonlinear-features-and-model-complexity.mp4 23.2 MB
data-machine-learning/02_preparing-your-data-for-machine-learning-success/02_coordinate/02_types-of-data.mp4 23.2 MB
machine-learning-applied/01_introduction-to-machine-learning-applications/02_lesson-2-supervised-learning/02_classification-what-is-it-and-how-does-it-work.mp4 23.1 MB
machine-learning-classification-algorithms/02_functions-for-fun-and-profit/01_finding-lines/02_optimal-line-fitting.mp4 22.9 MB
optimize-machine-learning-model-performance/02_responsible-machine-learning/01_feedback-fairness/01_ai-4-good-for-all.mp4 22.9 MB
machine-learning-classification-algorithms/02_functions-for-fun-and-profit/02_simple-vs-expressive/03_regularizers.mp4 22.9 MB
machine-learning-applied/01_introduction-to-machine-learning-applications/02_lesson-2-supervised-learning/03_regression-fitting-lines-and-predicting-numbers.mp4 22.9 MB
optimize-machine-learning-model-performance/01_machine-learning-strategy/02_ownership-products/02_build-buy-partner.mp4 22.6 MB
optimize-machine-learning-model-performance/04_care-and-feeding-of-your-machine-learning-system/03_scaling-up/02_dashboard-essentials-metrics-monitoring.mp4 22.5 MB
optimize-machine-learning-model-performance/04_care-and-feeding-of-your-machine-learning-system/01_mapping-the-model-lifecycle/01_mlpl-recap.mp4 22.4 MB
machine-learning-classification-algorithms/01_classification-using-decision-trees-and-k-nn/01_classification-in-a-nutshell/03_what-does-a-classifier-actually-do.mp4 22.1 MB
machine-learning-classification-algorithms/01_classification-using-decision-trees-and-k-nn/02_decision-trees/01_what-are-decision-trees.mp4 22.0 MB
machine-learning-applied/01_introduction-to-machine-learning-applications/02_lesson-2-supervised-learning/01_the-three-kinds-of-machine-learning.mp4 21.8 MB
data-machine-learning/01_what-does-good-data-look-like/02_know-your-data/02_metadata-matters.mp4 21.8 MB
data-machine-learning/04_bad-data/01_accept-limitations/01_imbalanced-data.mp4 21.5 MB
optimize-machine-learning-model-performance/02_responsible-machine-learning/02_you-are-what-you-optimize-design-considerations/02_secondary-effects-of-optimization.mp4 21.4 MB
data-machine-learning/02_preparing-your-data-for-machine-learning-success/03_clean-complete/04_data-cleaning-everybodys-favourite-task.mp4 21.3 MB
machine-learning-applied/03_learning-data/03_lesson-3-data-process/02_data-cleaning-everybodys-favourite-task.mp4 21.3 MB
data-machine-learning/04_bad-data/02_statistical-nuance/01_outliers.mp4 21.3 MB
data-machine-learning/03_feature-engineering-for-more-fun-profit/01_understanding-features/03_how-many-features.mp4 21.0 MB
machine-learning-classification-algorithms/04_contrasting-models/01_model-assessment/03_learning-curves.mp4 20.4 MB
machine-learning-applied/03_learning-data/02_lesson-2-data-relates-to-problems/01_ethical-issues.mp4 20.2 MB
optimize-machine-learning-model-performance/04_care-and-feeding-of-your-machine-learning-system/03_scaling-up/01_separating-datastack-from-production.mp4 19.9 MB
machine-learning-classification-algorithms/02_functions-for-fun-and-profit/01_finding-lines/03_loss-and-convexity.mp4 19.6 MB
optimize-machine-learning-model-performance/01_machine-learning-strategy/01_planning/03_risk-mitigation.mp4 19.6 MB
machine-learning-applied/02_machine-learning-in-the-real-world/03_lesson-3-getting-good-questions/02_identify-business-evaluation.mp4 19.5 MB
machine-learning-classification-algorithms/02_functions-for-fun-and-profit/01_finding-lines/01_line-fitting.mp4 19.2 MB
data-machine-learning/02_preparing-your-data-for-machine-learning-success/01_consolidate-sources/02_converting-to-useful-forms.mp4 18.9 MB
optimize-machine-learning-model-performance/01_machine-learning-strategy/01_planning/04_experimental-mindset.mp4 18.9 MB
optimize-machine-learning-model-performance/03_machine-learning-in-production-planning/01_design-considerations/02_users-break-things.mp4 18.9 MB
data-machine-learning/02_preparing-your-data-for-machine-learning-success/02_coordinate/03_aligning-similar-data.mp4 18.6 MB
data-machine-learning/01_what-does-good-data-look-like/03_matchmaking/01_identifying-data-from-problem.mp4 18.3 MB
data-machine-learning/02_preparing-your-data-for-machine-learning-success/01_consolidate-sources/04_how-much-data-do-i-need.mp4 18.2 MB
machine-learning-applied/03_learning-data/01_lesson-1-data-needs/02_how-much-data-do-i-need.mp4 18.2 MB
optimize-machine-learning-model-performance/03_machine-learning-in-production-planning/02_deployment-issues-operational-processes/01_when-do-i-retrain-the-model.mp4 18.2 MB
optimize-machine-learning-model-performance/03_machine-learning-in-production-planning/03_communicating-technical-content/01_knowledge-transfer.mp4 17.9 MB
optimize-machine-learning-model-performance/01_machine-learning-strategy/01_planning/02_ml-readiness.mp4 17.9 MB
machine-learning-applied/01_introduction-to-machine-learning-applications/01_lesson-1-definitions/01_introduction-to-the-applied-machine-learning-specialization.mp4 17.8 MB
optimize-machine-learning-model-performance/04_care-and-feeding-of-your-machine-learning-system/02_maintenance-checkpoints/02_quam-testing.mp4 17.8 MB
optimize-machine-learning-model-performance/03_machine-learning-in-production-planning/01_design-considerations/01_integrating-info-systems.mp4 17.7 MB
machine-learning-applied/01_introduction-to-machine-learning-applications/03_lesson-3-broader-machine-learning/01_unsupervised-learning.mp4 17.7 MB
data-machine-learning/03_feature-engineering-for-more-fun-profit/02_building-good-features/01_what-is-unsupervised-learning.mp4 17.6 MB
optimize-machine-learning-model-performance/01_machine-learning-strategy/03_teamwork-communication/01_setting-up-a-team.mp4 17.5 MB
machine-learning-applied/02_machine-learning-in-the-real-world/03_lesson-3-getting-good-questions/03_everything-is-a-proxy.mp4 17.5 MB
optimize-machine-learning-model-performance/04_care-and-feeding-of-your-machine-learning-system/02_maintenance-checkpoints/04_quam-updating.mp4 17.4 MB
data-machine-learning/02_preparing-your-data-for-machine-learning-success/03_clean-complete/01_imputing-missing-values.mp4 17.3 MB
optimize-machine-learning-model-performance/03_machine-learning-in-production-planning/03_communicating-technical-content/02_reporting-performance-to-stakeholders.mp4 17.1 MB
machine-learning-classification-algorithms/03_regression-for-classification-support-vector-machines/02_support-vector-machines/01_hinge-loss.mp4 16.9 MB
machine-learning-classification-algorithms/04_contrasting-models/03_parameter-tuning/01_parameter-tuning-and-grid-search.mp4 16.4 MB
optimize-machine-learning-model-performance/04_care-and-feeding-of-your-machine-learning-system/02_maintenance-checkpoints/03_quam-maintenance.mp4 15.9 MB
optimize-machine-learning-model-performance/03_machine-learning-in-production-planning/01_design-considerations/03_time-space-complexity-in-production.mp4 15.9 MB
optimize-machine-learning-model-performance/04_care-and-feeding-of-your-machine-learning-system/02_maintenance-checkpoints/01_quam-monitoring-and-logging.mp4 15.6 MB
optimize-machine-learning-model-performance/02_responsible-machine-learning/03_legalities-and-best-practices/01_regulatory-concerns.mp4 15.0 MB
machine-learning-applied/04_machine-learning-projects/01_lesson-1-machine-learning-process-lifecycle/01_mlpl-overview.mp4 14.8 MB
machine-learning-applied/02_machine-learning-in-the-real-world/03_lesson-3-getting-good-questions/01_broad-examples-narrowed-down.mp4 14.7 MB
machine-learning-classification-algorithms/04_contrasting-models/02_testing-and-validation-procedures/02_cross-validation.mp4 14.6 MB
optimize-machine-learning-model-performance/01_machine-learning-strategy/03_teamwork-communication/03_weekly-summary.mp4 14.6 MB
machine-learning-applied/03_learning-data/03_lesson-3-data-process/01_image-classification-example.mp4 14.5 MB
machine-learning-classification-algorithms/02_functions-for-fun-and-profit/03_from-regression-to-classification/02_weekly-summary.mp4 14.3 MB
data-machine-learning/01_what-does-good-data-look-like/01_know-your-problem/04_no-free-lunch-theorem.mp4 13.8 MB
data-machine-learning/04_bad-data/03_consequences-of-bad-data/01_badness-multipliers.mp4 13.3 MB
data-machine-learning/03_feature-engineering-for-more-fun-profit/01_understanding-features/02_useful-useless-features.mp4 13.2 MB
data-machine-learning/01_what-does-good-data-look-like/02_know-your-data/03_dealing-with-multimodal-data.mp4 13.2 MB
machine-learning-applied/02_machine-learning-in-the-real-world/02_lesson-2-applied-scenarios/03_what-to-consider-when-using-your-quam.mp4 13.2 MB
data-machine-learning/04_bad-data/01_accept-limitations/03_bias-in-data-sources.mp4 13.1 MB
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optimize-machine-learning-model-performance/02_responsible-machine-learning/03_legalities-and-best-practices/02_weekly-summary.mp4 12.8 MB
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machine-learning-classification-algorithms/04_contrasting-models/01_model-assessment/02_classification-assessment.mp4 12.4 MB
machine-learning-applied/04_machine-learning-projects/03_lesson-3-model-learning-and-evaluation/03_weekly-summary.mp4 12.3 MB
machine-learning-classification-algorithms/01_classification-using-decision-trees-and-k-nn/01_classification-in-a-nutshell/04_classification-in-scikit-learn.mp4 12.1 MB
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machine-learning-applied/01_introduction-to-machine-learning-applications/01_lesson-1-definitions/03_introduction-to-course-1.mp4 11.4 MB
machine-learning-classification-algorithms/03_regression-for-classification-support-vector-machines/01_models-with-transfer-functions/01_logistic-regression.mp4 11.3 MB
machine-learning-applied/02_machine-learning-in-the-real-world/03_lesson-3-getting-good-questions/05_weekly-summary.mp4 11.2 MB
optimize-machine-learning-model-performance/01_machine-learning-strategy/01_planning/01_introduction-to-the-course.mp4 11.1 MB
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data-machine-learning/02_preparing-your-data-for-machine-learning-success/01_consolidate-sources/03_data-quality.mp4 10.7 MB
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machine-learning-applied/03_learning-data/01_lesson-1-data-needs/01_sources-of-training-data.mp4 10.2 MB
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machine-learning-applied/04_machine-learning-projects/01_lesson-1-machine-learning-process-lifecycle/03_mlpl-as-experienced-by-farmer-betty.mp4 9.5 MB
data-machine-learning/02_preparing-your-data-for-machine-learning-success/03_clean-complete/03_weekly-summary-preparing-your-data-for-machine-learning-success.mp4 9.5 MB
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