Coursera - Introduction to Machine Learning in Production

Files Included :

01 specialization-overview.mp4 (42.68 MB)
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01 welcome.mp4 (21.29 MB)
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02 steps-of-an-ml-project.mp4 (9.62 MB)
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03 case-study-speech-recognition.mp4 (23.81 MB)
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04 course-outline.mp4 (6.71 MB)
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01 key-challenges.mp4 (25.7 MB)
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02 deployment-patterns.mp4 (20.43 MB)
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03 monitoring.mp4 (18.46 MB)
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04 pipeline-monitoring.mp4 (16.51 MB)
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01 modeling-overview.mp4 (10.04 MB)
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02 key-challenges.mp4 (9.22 MB)
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03 why-low-average-error-isn-t-good-enough.mp4 (17.96 MB)
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04 establish-a-baseline.mp4 (16.58 MB)
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05 tips-for-getting-started.mp4 (11.05 MB)
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01 error-analysis-example.mp4 (13.98 MB)
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02 prioritizing-what-to-work-on.mp4 (10.18 MB)
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03 skewed-datasets.mp4 (20.13 MB)
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04 performance-auditing.mp4 (16.15 MB)
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01 data-centric-ai-development.mp4 (8.09 MB)
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02 a-useful-picture-of-data-augmentation.mp4 (11.49 MB)
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03 data-augmentation.mp4 (16.65 MB)
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04 can-adding-data-hurt.mp4 (15.13 MB)
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05 adding-features.mp4 (18.47 MB)
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06 experiment-tracking.mp4 (9.22 MB)
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07 from-big-data-to-good-data.mp4 (8.55 MB)
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01 why-is-data-definition-hard.mp4 (10.51 MB)
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02 more-label-ambiguity-examples.mp4 (14.58 MB)
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03 major-types-of-data-problems.mp4 (20.2 MB)
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04 small-data-and-label-consistency.mp4 (15.49 MB)
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05 improving-label-consistency.mp4 (16.47 MB)
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06 human-level-performance-hlp.mp4 (18.51 MB)
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07 raising-hlp.mp4 (22.83 MB)
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01 obtaining-data.mp4 (20.5 MB)
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02 data-pipeline.mp4 (10.93 MB)
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03 meta-data-data-provenance-and-lineage.mp4 (16.21 MB)
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04 balanced-train-dev-test-splits.mp4 (11.13 MB)
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01 what-is-scoping.mp4 (8.64 MB)
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02 scoping-process.mp4 (13.91 MB)
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03 diligence-on-feasibility-and-value.mp4 (22.87 MB)
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04 diligence-on-value.mp4 (13.5 MB)
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05 milestones-and-resourcing.mp4 (4.81 MB)
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