ECML-PKDD Applied (ADS) Track: Difference between revisions
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(Created page with "A ECML-PKDD Applied (ADS) Track is an applied conference track within an ECML-PKDD conference. * <B>Context:</B> ** It can (typically) be composed of ECML-PKDD ADS Papers that focus on Machine Learning Applications, Data Science, and Knowledge Discovery methodologies to solve real-world problems. ** It can (typically) involve ECML-PKDD ADS Paper Reviews. ** It can (typically) provide a platform for researchers and practitioners to pr...") |
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Latest revision as of 12:30, 19 April 2024
A ECML-PKDD Applied (ADS) Track is an applied conference track within an ECML-PKDD conference.
- Context:
- It can (typically) be composed of ECML-PKDD ADS Papers that focus on Machine Learning Applications, Data Science, and Knowledge Discovery methodologies to solve real-world problems.
- It can (typically) involve ECML-PKDD ADS Paper Reviews.
- It can (typically) provide a platform for researchers and practitioners to present their findings on how machine learning and data mining techniques can be applied in real-world scenarios.
- It can (often) focus on applying novel solutions to practical problems.
- It can encourage submissions that detail the deployment of machine learning models in real settings, discussing not only the performance of the model but also implementation challenges and deployment outcomes.
- ...
- Example(s):
- Counter-Example(s):
- See: ECML PKDD, Real-World Machine Learning Applications, Knowledge Discovery in Databases, Data Mining