Welcome! Please contribute your ideas for what challenges we might aspire to solve, changes in our community that can improve machine learning impact, and examples of machine learning projects that have had tangible impact.
Lacking context for this site? Read the original paper: Machine Learning that Matters (ICML 2012). You can also review the slides.
mlcomp.org for replication and comparison
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Kiri's talk today said that the ML community doesn't have standards for replicability. Relatedly, one of the questioners complained that published algorithms are very hard to reimplement and use.
But how about mlcomp.org, started a year or two ago by Percy Liang and Jake Abernethy? It lets you try new algorithms on existing datasets, and existing algorithms on new datasets. It's not limited to classification; it supports several types of problems with appropriate metrics, as well as problem reductions.
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