Data Labeling for Machine Learning

Files Included :

01 - The need for data labeling.mp4 (7.25 MB)
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01 - The data labeling process.mp4 (4.74 MB)
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02 - Approaches to data labeling.mp4 (5.98 MB)
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03 - Data labeling challenges, best practices, and use cases.mp4 (3.78 MB)
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04 - Data labeling with Azure ML.mp4 (2.87 MB)
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05 - Setting up an Azure ML workspace.mp4 (6.79 MB)
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06 - Setting up an image labeling project Creating data assets.mp4 (11.38 MB)
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07 - Setting up an image labeling project Configuring settings.mp4 (10.68 MB)
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08 - Manual image labeling and review.mp4 (10.88 MB)
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09 - Manual labeling progress checks.mp4 (7.73 MB)
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01 - Automated machine learning for image classification.mp4 (12.02 MB)
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02 - Examining model training metrics.mp4 (8 MB)
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03 - Data labeling project insights.mp4 (5.46 MB)
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04 - ML assisted labeling with clustering and pre-labeling.mp4 (7.57 MB)
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05 - Configuring inference for new training runs.mp4 (6.38 MB)
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06 - Exploring the labeled dataset.mp4 (5.98 MB)
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01 - Programmatic labeling with Snorkel.mp4 (8.6 MB)
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02 - Installing Python libraries.mp4 (8.99 MB)
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03 - Exploring the spam ham dataset.mp4 (15.42 MB)
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04 - Writing and analyzing labeling functions.mp4 (15.31 MB)
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05 - Exploring other labeling functions.mp4 (12.29 MB)
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06 - Programmatic labeling using the majority label voter.mp4 (7.1 MB)
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07 - Scoring and comparing the label models.mp4 (8.76 MB)
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01 - Increasing the number of labeling functions.mp4 (11.29 MB)
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02 - Using sentiment and parts of speech tagging in labeling functions.mp4 (18.86 MB)
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03 - Evaluating labeling function metrics on test data.mp4 (7.71 MB)
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04 - Using all labeling functions to label data.mp4 (16.45 MB)
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05 - Training a classifier on programmatically generated labels.mp4 (5.26 MB)
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01 - Summary and next steps.mp4 (1.77 MB)
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