Coursera - Machine Learning Engineering for Production (MLOps) Specialization

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Files Included :

01 welcome.mp4 (20.35 MB)
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04 course-outline.mp4 (6.44 MB)
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01 key-challenges.mp4 (25.62 MB)
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03 deployment-patterns.mp4 (20.05 MB)
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04 monitoring.mp4 (18.25 MB)
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05 pipeline-monitoring.mp4 (16.17 MB)
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01 modeling-overview.mp4 (9.4 MB)
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02 key-challenges.mp4 (8.98 MB)
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03 why-low-average-error-isn-t-good-enough.mp4 (18.07 MB)
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04 establish-a-baseline.mp4 (15.99 MB)
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05 tips-for-getting-started.mp4 (11.07 MB)
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01 error-analysis-example.mp4 (13.74 MB)
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02 prioritizing-what-to-work-on.mp4 (10.23 MB)
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03 skewed-datasets.mp4 (20.11 MB)
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04 performance-auditing.mp4 (15.76 MB)
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01 data-centric-ai-development.mp4 (7.52 MB)
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02 a-useful-picture-of-data-augmentation.mp4 (11.36 MB)
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03 data-augmentation.mp4 (16.04 MB)
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04 can-adding-data-hurt.mp4 (14.57 MB)
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05 adding-features.mp4 (18.1 MB)
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06 experiment-tracking.mp4 (8.86 MB)
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07 from-big-data-to-good-data.mp4 (8.52 MB)
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01 why-is-data-definition-hard.mp4 (10.06 MB)
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02 more-label-ambiguity-examples.mp4 (14.53 MB)
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03 major-types-of-data-problems.mp4 (20 MB)
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04 small-data-and-label-consistency.mp4 (15.3 MB)
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05 improving-label-consistency.mp4 (16.04 MB)
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06 human-level-performance-hlp.mp4 (18.51 MB)
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07 raising-hlp.mp4 (21.81 MB)
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01 obtaining-data.mp4 (20.71 MB)
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02 data-pipeline.mp4 (10.66 MB)
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03 meta-data-data-provenance-and-lineage.mp4 (16.09 MB)
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04 balanced-train-dev-test-splits.mp4 (10.81 MB)
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01 what-is-scoping.mp4 (8.11 MB)
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02 scoping-process.mp4 (13.49 MB)
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03 diligence-on-feasibility-and-value.mp4 (23.23 MB)
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04 diligence-on-value.mp4 (13.19 MB)
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05 milestones-and-resourcing.mp4 (4.78 MB)
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01 importance-of-data.mp4 (12.61 MB)
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02 example-application-suggesting-runs.mp4 (10.98 MB)
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03 responsible-data-security-privacy-fairness.mp4 (14.8 MB)
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01 case-study-degraded-model-performance.mp4 (15.02 MB)
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02 data-and-concept-change-in-production-ml.mp4 (8.08 MB)
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03 process-feedback-and-human-labeling.mp4 (14.56 MB)
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01 detecting-data-issues.mp4 (12.44 MB)
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02 tensorflow-data-validation.mp4 (8.82 MB)
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01 introduction-to-preprocessing.mp4 (10.05 MB)
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02 preprocessing-operations.mp4 (11.82 MB)
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03 feature-engineering-techniques.mp4 (20.32 MB)
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04 feature-crosses.mp4 (5.28 MB)
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02 tensorflow-transform.mp4 (17.53 MB)
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01 feature-spaces.mp4 (6.32 MB)
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02 feature-selection.mp4 (5.71 MB)
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03 filter-methods.mp4 (8.01 MB)
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04 wrapper-methods.mp4 (7.13 MB)
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05 embedded-methods.mp4 (7.49 MB)
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01 data-journey.mp4 (10.6 MB)
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02 introduction-to-ml-metadata.mp4 (13.16 MB)
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03 ml-metadata-in-action.mp4 (6.19 MB)
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01 schema-development.mp4 (6.1 MB)
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02 schema-environments.mp4 (5.08 MB)
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01 feature-stores.mp4 (10.96 MB)
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02 data-warehouse.mp4 (5.92 MB)
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03 data-lakes.mp4 (4.75 MB)
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01 intro-to-automl.mp4 (7.9 MB)
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02 understanding-search-spaces.mp4 (2.68 MB)
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03 search-strategies.mp4 (6.78 MB)
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05 measuring-automl-efficacy.mp4 (5.37 MB)
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06 automl-on-the-cloud.mp4 (11.84 MB)
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02 curse-of-dimensionality.mp4 (13.83 MB)
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03 curse-of-dimensionality-an-example.mp4 (6.47 MB)
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04 manual-dimensionality-reduction.mp4 (7.6 MB)
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08 principal-components-analysis.mp4 (12.78 MB)
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09 other-techniques.mp4 (10.83 MB)
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01 mobile-iot-and-similar-use-cases.mp4 (10.18 MB)
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03 post-training-quantization.mp4 (8.65 MB)
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04 quantization-aware-training.mp4 (6.26 MB)
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06 pruning.mp4 (20.42 MB)
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01 distributed-training.mp4 (15.94 MB)
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03 high-performance-ingestion.mp4 (15.77 MB)
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01 teacher-and-student-networks.mp4 (4.35 MB)
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02 knowledge-distillation-techniques.mp4 (12.35 MB)
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01 model-performance-analysis.mp4 (15.69 MB)
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01 introduction-to-tensorflow-model-analysis.mp4 (9.24 MB)
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02 tfma-in-practice.mp4 (5.52 MB)
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04 model-debugging-overview.mp4 (4.72 MB)
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05 benchmark-models.mp4 (1.57 MB)
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06 sensitivity-analysis-and-adversarial-attacks.mp4 (13.76 MB)
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07 adversarial-attack-demo.mp4 (11.36 MB)
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09 residual-analysis.mp4 (3.09 MB)
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10 model-remediation.mp4 (6.21 MB)
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11 fairness.mp4 (5.27 MB)
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12 measuring-fairness.mp4 (8.01 MB)
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01 continuous-evaluation-and-monitoring.mp4 (23.54 MB)
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01 explainable-ai.mp4 (11.59 MB)
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01 model-interpretation-methods.mp4 (13.01 MB)
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02 intrinsically-interpretable-models.mp4 (14.78 MB)
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01 model-agnostic-methods.mp4 (2.46 MB)
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02 partial-dependence-plots.mp4 (7.41 MB)
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03 permutation-feature-importance.mp4 (4.47 MB)
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06 shapley-values.mp4 (10.21 MB)
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07 shapley-additive-explanations-shap.mp4 (4.9 MB)
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10 testing-concept-activation-vectors.mp4 (5.53 MB)
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11 lime.mp4 (2.11 MB)
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13 ai-explanations.mp4 (10.35 MB)
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01 introduction-to-model-serving.mp4 (10.84 MB)
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02 deployment-options.mp4 (5.24 MB)
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01 installing-tensorflow-serving.mp4 (9.59 MB)
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01 model-serving-architecture.mp4 (9.08 MB)
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03 model-servers-other-providers.mp4 (11.94 MB)
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01 scaling-infrastructure.mp4 (25.03 MB)
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01 online-inference.mp4 (12.9 MB)
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01 data-preprocessing.mp4 (9.4 MB)
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01 batch-inference-scenarios.mp4 (9.04 MB)
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01 batch-processing-with-etl.mp4 (7.36 MB)
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01 experiment-tracking.mp4 (14.78 MB)
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01 mlops-level-0.mp4 (7.91 MB)
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02 mlops-levels-1-2.mp4 (26.8 MB)
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05 developing-components-for-an-orchestrated-workflow.mp4 (19.31 MB)
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04 continuous-delivery.mp4 (10.92 MB)
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07 progressive-delivery.mp4 (12.55 MB)
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01 why-monitoring-matters.mp4 (11.85 MB)
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02 observability-in-ml.mp4 (6.81 MB)
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03 monitoring-targets-in-ml.mp4 (5.93 MB)
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04 logging-for-ml-monitoring.mp4 (9.91 MB)
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05 tracing-for-ml-systems.mp4 (4.26 MB)
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01 what-is-model-decay.mp4 (5.05 MB)
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02 model-decay-detection.mp4 (3.85 MB)
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03 ways-to-mitigate-model-decay.mp4 (8.57 MB)
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01 responsible-ai.mp4 (7.44 MB)
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03 legal-requirements-for-secure-and-private-ai.mp4 (14.77 MB)
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05 anonymization-and-pseudonymisation.mp4 (5.82 MB)
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06 right-to-be-forgotten.mp4 (15.04 MB)
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01 specialization-recap-and-farewell.mp4 (5.59 MB)
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