Tutorial for ATCII Lifelong Learning Job #401
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Welcome @qxygxt! It looks like this is your first PR to kubeedge/sedna 🎉 |
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The current version of tutorial has been review on the routine meeting of SIG AI, which looks good to me. BTW: Sign is needed in commit. |
Toturial based on lifelong learning job in thermal comfort prediction scenario to explain how to run the default example with customized configurations, as well as how to develop and integrate user-defined modules. Signed-off-by: qxygxt <xingyu.q@outlook.com>
Signed-off-by: qxygxt <xingyu.q@outlook.com>
Signed-off-by: qxygxt <xingyu.q@outlook.com>
Signed-off-by: qxygxt <xingyu.q@outlook.com>
Signed-off-by: qxygxt <xingyu.q@outlook.com>
Signed-off-by: qxygxt <xingyu.q@outlook.com>
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| Artifacts including multi-task learning models, partitioned sample sets, etc. can be found in `outputDir`, and the inference result is stored in the `Dataset`'s url. | ||
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| # 2 Develop and Integrate Customized Modules |
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This tutorial not only shows how to run the default example (with or without customized configurations), but also shows how to develop and integrate user-defined modules. That is indeed impressive.
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/lgtm |
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Please squash the 7 commits to 1 commits to make the commit history more clean. |
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New changes are detected. LGTM label has been removed. |
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In this PR, a tutorial based on lifelong learning job in thermal comfort prediction scenario will explain how to run the default example with customized configurations, as well as how to develop and integrate user-defined modules to users.