Report on last executions.
100% 2019-02-18
| index | coverage | exe time | last execution | name | title | success | time | nb cells | nb runs | nb valid |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 100% | 3.784 | 2019-02-18 | 101/100_Logistic_IRIS.ipynb | 100 - Logistic Regression with IRIS and pytorch | True | 5.237 | 9 | 9 | 9 |
| 1 | 100% | 4.612 | 2019-02-18 | 101/110_Perceptron_Iris.ipynb | 110 - First percepton with pytorch | True | 6.053 | 9 | 9 | 9 |
| 2 | 100% | 61.688 | 2019-02-18 | 101/200_Perceptron_MNIST.ipynb | 200 - First percepton with pytorch | True | 63.109 | 14 | 14 | 14 |
| 3 | 100% | 7087.991 | 2019-02-18 | 101/210_Convolution_MNIST.ipynb | 210 - First convolution network (CNN) with pytorch | True | 7090.483 | 13 | 13 | 13 |
| 4 | 100% | 5031.327 | 2019-02-18 | 101/300_Convolution_CIFAR10.ipynb | 300 - Convolution network, gradient, tweaks, with pytorch | True | 5033.469 | 12 | 12 | 12 |
| 5 | 100% | 69.370 | 2019-02-18 | 101/ml_deep_python.ipynb | 2A.dl - Deep learning avec Python | True | 71.177 | 11 | 11 | 11 |
| 6 | 100% | 1.400 | 2019-02-18 | cheat_sheet/chsh_images.ipynb | Images et matrices | True | 3.057 | 16 | 16 | 16 |
