aws-solutions / maintaining-personalized-experiences-with-machine-learning
The Maintaining Personalized Experiences with Machine Learning solution provides an automated pipeline to maintain resources in Amazon Personalize. This pipeline allows you to keep up to date with your user???s most recent activity while sustaining and improving the relevance of recommendations
Summary
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| Main Code: 9,104 LOC (188 files) = PY (99%) + JAVA (<1%) Secondary code: Test: 3,718 LOC (60); Generated: 0 LOC (0); Build & Deploy: 81 LOC (3); Other: 1,007 LOC (11); |
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| Duplication: 24% | |||
| File Size: 0% long (>1000 LOC), 63% short (<= 200 LOC) | |||
| Unit Size: 11% long (>100 LOC), 60% short (<= 10 LOC) | |||
| Conditional Complexity: 0% complex (McCabe index > 50), 72% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (25 components) | ||
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4 months old
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0% of code updated more than 50 times Also see temporal dependencies for files frequently changed in same commits. |
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| Goals: Keep the system simple and easy to change (4) | |||
Latest commit date: 2022-01-27
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3
commits
(30 days)
2
contributors
(30 days) |
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