Table 1: Algorithm usage by Employment Type
Employment Type | % Voters | Avg Num Algorithms Used | % Used Super- vised | % Used Unsuper- vised | % Used Meta | % Used Other Methods |
---|---|---|---|---|---|---|
Industry | 59% | 8.4 | 94% | 81% | 55% | 83% |
Government/Non-profit | 4.1% | 9.5 | 91% | 89% | 49% | 89% |
Student | 16% | 8.1 | 94% | 76% | 47% | 77% |
Academia | 12% | 7.2 | 95% | 81% | 44% | 77% |
All | 8.3 | 94% | 82% | 48% | 81% |
Table 2: Top 10 Algorithms + Deep Learning usage by Employment Type
Algorithm | Industry | Government/Non-profit | Academia | Student | All |
---|---|---|---|---|---|
Regression | 71% | 63% | 51% | 64% | 67% |
Clustering | 58% | 63% | 51% | 58% | 57% |
Decision | 59% | 63% | 38% | 57% | 55% |
Visualization | 55% | 71% | 28% | 47% | 49% |
K-NN | 46% | 54% | 48% | 47% | 46% |
PCA | 43% | 57% | 48% | 40% | 43% |
Statistics | 47% | 49% | 37% | 36% | 43% |
Random Forests | 40% | 40% | 29% | 36% | 38% |
Time series | 42% | 54% | 26% | 24% | 37% |
Text Mining | 36% | 40% | 33% | 38% | 36% |
Deep Learning | 18% | 9% | 24% | 19% | 19% |
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