Notebooks Coverage#
Report on last executions.
95% 2023-04-28
index |
coverage |
exe time |
last execution |
name |
title |
success |
time |
nb cells |
nb runs |
nb valid |
---|---|---|---|---|---|---|---|---|---|---|
0 |
100% |
22.998 |
2023-04-28 |
1A.1 - Liste, tuple, ensemble, dictionnaire, liste chaînée, coût des opérations |
True |
27.202 |
4 |
4 |
4 |
|
1 |
100% |
9.752 |
2023-04-28 |
True |
13.843 |
12 |
12 |
12 |
||
2 |
100% |
12.371 |
2023-04-28 |
True |
16.507 |
23 |
23 |
23 |
||
3 |
100% |
0.606 |
2023-04-28 |
1A.algo - Calculer le nombre de façons de monter une échelle. |
True |
4.678 |
6 |
6 |
6 |
|
4 |
100% |
1.888 |
2023-04-28 |
True |
6.030 |
16 |
16 |
16 |
||
5 |
100% |
5.175 |
2023-04-28 |
True |
9.286 |
15 |
15 |
15 |
||
6 |
100% |
0.337 |
2023-04-28 |
True |
4.466 |
4 |
4 |
4 |
||
7 |
100% |
0.810 |
2023-04-28 |
True |
4.890 |
8 |
8 |
8 |
||
8 |
100% |
72.472 |
2023-04-28 |
True |
76.589 |
15 |
15 |
15 |
||
9 |
100% |
46.691 |
2023-04-28 |
True |
50.770 |
10 |
10 |
10 |
||
10 |
100% |
14.745 |
2023-04-28 |
True |
18.834 |
11 |
11 |
11 |
||
11 |
100% |
0.990 |
2023-04-28 |
True |
5.057 |
9 |
9 |
9 |
||
12 |
100% |
5.274 |
2023-04-28 |
True |
9.472 |
29 |
29 |
29 |
||
13 |
100% |
2.168 |
2023-04-28 |
True |
6.271 |
8 |
8 |
8 |
||
14 |
100% |
84.972 |
2023-04-28 |
True |
89.109 |
17 |
17 |
17 |
||
15 |
100% |
361.351 |
2023-04-24 |
True |
365.484 |
28 |
28 |
28 |
||
16 |
100% |
19.751 |
2023-04-24 |
True |
23.905 |
16 |
16 |
16 |
||
17 |
100% |
11.917 |
2023-04-24 |
True |
16.052 |
26 |
26 |
26 |
||
18 |
100% |
81.697 |
2023-04-24 |
True |
85.803 |
22 |
22 |
22 |
||
19 |
100% |
28.510 |
2023-04-28 |
True |
32.650 |
20 |
20 |
20 |
||
20 |
100% |
44.084 |
2023-04-24 |
True |
48.191 |
43 |
43 |
43 |
||
21 |
89% |
3.220 |
2023-04-28 |
True |
7.677 |
28 |
25 |
25 |
||
22 |
100% |
9.404 |
2023-04-28 |
True |
13.626 |
29 |
29 |
29 |
||
23 |
100% |
8.123 |
2023-04-28 |
True |
12.359 |
21 |
21 |
21 |
||
24 |
100% |
1.079 |
2023-04-28 |
True |
5.299 |
11 |
11 |
11 |
||
25 |
100% |
14.444 |
2023-04-28 |
True |
18.726 |
20 |
20 |
20 |
||
26 |
100% |
226.565 |
2023-04-28 |
True |
230.707 |
19 |
19 |
19 |
||
27 |
0% |
nan |
nan |
68 |
0 |
|||||
28 |
100% |
16.889 |
2023-04-28 |
True |
21.413 |
19 |
19 |
19 |
||
29 |
100% |
192.462 |
2023-04-24 |
True |
196.723 |
92 |
92 |
92 |
||
30 |
100% |
4.544 |
2023-04-28 |
True |
8.703 |
15 |
15 |
15 |
||
31 |
100% |
8.048 |
2023-04-28 |
True |
12.213 |
23 |
23 |
23 |
||
32 |
100% |
1.738 |
2023-04-28 |
True |
5.866 |
5 |
5 |
5 |
||
33 |
100% |
25.726 |
2023-04-28 |
True |
29.928 |
28 |
28 |
28 |
||
34 |
100% |
6.760 |
2023-04-28 |
True |
10.926 |
8 |
8 |
8 |
||
35 |
100% |
118.470 |
2023-04-24 |
2A.i - Données non structurées, programmation fonctionnelle : dask |
True |
123.075 |
16 |
16 |
16 |
|
36 |
100% |
26.184 |
2023-04-24 |
True |
30.342 |
20 |
20 |
20 |
||
37 |
100% |
280.375 |
2023-04-24 |
True |
284.569 |
44 |
44 |
44 |
||
38 |
100% |
64.137 |
2023-04-28 |
True |
68.331 |
27 |
27 |
27 |
||
39 |
100% |
2195.008 |
2023-04-24 |
True |
2201.026 |
21 |
21 |
21 |
||
40 |
100% |
23.566 |
2023-04-24 |
True |
27.572 |
14 |
14 |
14 |
||
41 |
100% |
1.306 |
2023-04-28 |
1A.e - Correction de l’interrogation écrite du 26 septembre 2014 |
True |
5.453 |
12 |
12 |
12 |
|
42 |
100% |
3.386 |
2023-04-28 |
1A.e - Correction de l’interrogation écrite du 10 octobre 2014 |
True |
7.532 |
17 |
17 |
17 |
|
43 |
82% |
3.438 |
2023-04-28 |
1A.e - Correction de l’interrogation écrite du 14 novembre 2014 |
True |
7.696 |
35 |
29 |
29 |
|
44 |
100% |
1.472 |
2023-04-28 |
1A.e - Correction de l’interrogation écrite du 14 novembre 2014 |
True |
5.586 |
15 |
15 |
15 |
|
45 |
100% |
0.816 |
2023-04-28 |
1A.e - Correction de l’interrogation écrite du 26 septembre 2015 |
True |
4.928 |
12 |
12 |
12 |
|
46 |
100% |
1.333 |
2023-04-28 |
1A.e - Correction de l’interrogation écrite du 6 novembre 2015 |
True |
5.497 |
16 |
16 |
16 |
|
47 |
100% |
27.062 |
2023-04-28 |
1A.e - TD noté, 27 novembre 2012 (éléments de code pour le coloriage) |
True |
31.153 |
6 |
6 |
6 |
|
48 |
100% |
59.744 |
2023-04-28 |
True |
63.934 |
14 |
14 |
14 |
||
49 |
100% |
4.513 |
2023-04-28 |
True |
8.733 |
36 |
36 |
36 |
||
50 |
100% |
0.216 |
2023-04-28 |
True |
4.390 |
6 |
6 |
6 |
||
51 |
100% |
10.965 |
2023-04-28 |
True |
15.261 |
26 |
26 |
26 |
||
52 |
100% |
3.798 |
2023-04-28 |
True |
8.085 |
23 |
23 |
23 |
||
53 |
100% |
2.861 |
2023-04-28 |
True |
7.093 |
21 |
21 |
21 |
||
54 |
100% |
20.921 |
2023-04-28 |
True |
25.170 |
25 |
25 |
25 |
||
55 |
100% |
18.349 |
2023-04-28 |
True |
22.737 |
21 |
21 |
21 |
||
56 |
100% |
81.205 |
2023-04-28 |
True |
85.340 |
17 |
17 |
17 |
||
57 |
100% |
40.708 |
2023-04-28 |
True |
44.859 |
18 |
18 |
18 |
||
58 |
100% |
18.894 |
2023-04-28 |
True |
23.116 |
29 |
29 |
29 |
||
59 |
100% |
17.336 |
2023-04-28 |
True |
21.540 |
28 |
28 |
28 |
||
60 |
100% |
27.205 |
2023-04-28 |
True |
31.362 |
24 |
24 |
24 |
||
61 |
100% |
39.366 |
2023-04-28 |
True |
43.752 |
31 |
31 |
31 |
||
62 |
100% |
1.143 |
2023-04-28 |
True |
5.273 |
9 |
9 |
9 |
||
63 |
100% |
9.732 |
2023-04-28 |
True |
14.006 |
10 |
10 |
10 |
||
64 |
100% |
53.322 |
2023-04-28 |
True |
57.563 |
17 |
17 |
17 |
||
65 |
100% |
52.237 |
2023-04-28 |
True |
56.457 |
39 |
39 |
39 |
||
66 |
100% |
21.336 |
2023-04-28 |
True |
25.448 |
11 |
11 |
11 |
||
67 |
100% |
7.024 |
2023-04-28 |
True |
11.185 |
6 |
6 |
6 |
||
68 |
100% |
7.000 |
2023-04-28 |
True |
11.407 |
11 |
11 |
11 |
||
69 |
100% |
1.148 |
2023-04-28 |
3A.mr - Random Walk with Restart (système de recommandations) |
True |
5.378 |
4 |
4 |
4 |
|
70 |
100% |
3.007 |
2023-04-24 |
True |
7.055 |
9 |
9 |
9 |
||
71 |
100% |
34.735 |
2023-04-28 |
True |
38.891 |
14 |
14 |
14 |
||
72 |
100% |
65.558 |
2023-04-28 |
True |
70.146 |
15 |
15 |
15 |
||
73 |
0% |
nan |
nan |
30 |
0 |
|||||
74 |
100% |
2541.043 |
2023-04-24 |
True |
2545.287 |
24 |
24 |
24 |
||
75 |
100% |
811.466 |
2023-04-24 |
True |
815.733 |
35 |
35 |
35 |
||
76 |
100% |
8.624 |
2023-04-28 |
sklearn_ensae_course/00_introduction_machine_learning_and_data.ipynb |
True |
12.796 |
13 |
13 |
13 |
|
77 |
100% |
8.990 |
2023-04-28 |
2A.ML101.1: Introduction to data manipulation with scientific Python |
True |
13.124 |
18 |
18 |
18 |
|
78 |
100% |
18.917 |
2023-04-28 |
sklearn_ensae_course/02_basic_of_machine_learning_with_scikit-learn.ipynb |
2A.ML101.2: Basic principles of machine learning with scikit-learn |
True |
23.039 |
15 |
15 |
15 |
79 |
100% |
36.757 |
2023-04-28 |
2A.ML101.3: Supervised Learning: Classification of Handwritten Digits |
True |
40.874 |
12 |
12 |
12 |
|
80 |
100% |
18.586 |
2023-04-28 |
True |
22.747 |
12 |
12 |
12 |
||
81 |
100% |
25.285 |
2023-04-28 |
sklearn_ensae_course/05_measuring_prediction_performance.ipynb |
True |
29.733 |
23 |
23 |
23 |
|
82 |
100% |
26.361 |
2023-04-28 |
2A.ML101.6: Unsupervised Learning: Dimensionality Reduction and Visualization |
True |
30.485 |
18 |
18 |
18 |
|
83 |
100% |
29.202 |
2023-04-28 |
sklearn_ensae_course/07_application_to_face_recognition.ipynb |
True |
33.370 |
19 |
19 |
19 |
|
84 |
100% |
18.045 |
2023-04-28 |
sklearn_ensae_course/08_validation_and_learning_curves.ipynb |
True |
22.179 |
15 |
15 |
15 |
|
85 |
100% |
0.545 |
2023-04-28 |
True |
4.695 |
6 |
6 |
6 |
||
86 |
100% |
8.009 |
2023-04-28 |
True |
12.163 |
30 |
30 |
30 |
||
87 |
100% |
0.338 |
2023-04-28 |
True |
4.414 |
3 |
3 |
3 |
||
88 |
100% |
1.356 |
2023-04-28 |
True |
5.496 |
11 |
11 |
11 |
||
89 |
100% |
62.801 |
2023-04-28 |
True |
66.999 |
20 |
20 |
20 |
||
90 |
100% |
0.330 |
2023-04-28 |
True |
4.451 |
5 |
5 |
5 |
||
91 |
100% |
0.715 |
2023-04-28 |
True |
4.820 |
7 |
7 |
7 |
||
92 |
75% |
1.265 |
2023-04-28 |
True |
5.383 |
16 |
12 |
12 |
||
93 |
100% |
3.309 |
2023-04-28 |
True |
7.494 |
30 |
30 |
30 |
||
94 |
100% |
1.900 |
2023-04-28 |
True |
6.036 |
26 |
26 |
26 |
||
95 |
100% |
4.477 |
2023-04-28 |
True |
8.741 |
20 |
20 |
20 |
||
96 |
100% |
1.571 |
2023-04-28 |
1A.2 - Classes, méthodes, attributs, opérateurs et carré magique |
True |
5.774 |
17 |
17 |
17 |
|
97 |
100% |
1.066 |
2023-04-28 |
True |
5.169 |
11 |
11 |
11 |
||
98 |
100% |
1.287 |
2023-04-28 |
True |
5.436 |
13 |
13 |
13 |
||
99 |
100% |
0.889 |
2023-04-28 |
True |
4.981 |
8 |
8 |
8 |
||
100 |
100% |
0.890 |
2023-04-28 |
1A.1 - Dictionnaires, fonctions, code de Vigenère (correction) |
True |
4.982 |
9 |
9 |
9 |
|
101 |
100% |
6.606 |
2023-04-28 |
1A.2 - Modules, fichiers, expressions régulières (correction) |
True |
10.704 |
20 |
20 |
20 |
|
102 |
100% |
64.177 |
2023-04-28 |
1A.2 - Classes, méthodes, attributs, opérateurs et carré magique (correction) |
True |
68.282 |
12 |
12 |
12 |
|
103 |
100% |
0.706 |
2023-04-28 |
True |
4.793 |
5 |
5 |
5 |
||
104 |
100% |
2.765 |
2023-04-28 |
True |
6.899 |
5 |
5 |
5 |
||
105 |
100% |
7.456 |
2023-04-28 |
True |
11.582 |
11 |
11 |
11 |
||
106 |
100% |
1.825 |
2023-04-28 |
True |
5.969 |
6 |
6 |
6 |
||
107 |
100% |
21.223 |
2023-04-28 |
True |
25.442 |
23 |
23 |
23 |
||
108 |
100% |
0.412 |
2023-04-28 |
True |
4.485 |
4 |
4 |
4 |
||
109 |
100% |
1.806 |
2023-04-28 |
True |
5.929 |
8 |
8 |
8 |
||
110 |
100% |
2.349 |
2023-04-28 |
True |
6.718 |
9 |
9 |
9 |
||
111 |
100% |
1.206 |
2023-04-28 |
True |
5.320 |
6 |
6 |
6 |
||
112 |
100% |
1.557 |
2023-04-28 |
True |
5.660 |
6 |
6 |
6 |
||
113 |
100% |
2.543 |
2023-04-28 |
True |
6.703 |
11 |
11 |
11 |
||
114 |
100% |
0.167 |
2023-04-28 |
True |
4.256 |
4 |
4 |
4 |
||
115 |
100% |
4.722 |
2023-04-28 |
True |
8.898 |
17 |
17 |
17 |
||
116 |
100% |
0.432 |
2023-04-28 |
True |
4.632 |
8 |
8 |
8 |
||
117 |
100% |
0.512 |
2023-04-28 |
True |
4.627 |
10 |
10 |
10 |
||
118 |
100% |
0.141 |
2023-04-28 |
True |
4.280 |
4 |
4 |
4 |
||
119 |
100% |
0.570 |
2023-04-28 |
True |
4.674 |
6 |
6 |
6 |
||
120 |
100% |
21.370 |
2023-04-28 |
True |
25.516 |
17 |
17 |
17 |
||
121 |
100% |
8.447 |
2023-04-28 |
1A.algo - Programmation dynamique et plus court chemin (correction) |
True |
12.607 |
15 |
15 |
15 |
|
122 |
100% |
3.625 |
2023-04-28 |
True |
7.835 |
20 |
20 |
20 |
||
123 |
100% |
177.167 |
2023-04-24 |
True |
181.418 |
20 |
20 |
20 |
||
124 |
100% |
4.249 |
2023-04-28 |
True |
8.474 |
5 |
5 |
5 |
||
125 |
100% |
1.928 |
2023-04-28 |
True |
6.032 |
7 |
7 |
7 |
||
126 |
100% |
0.000 |
2023-04-28 |
True |
4.076 |
1 |
1 |
1 |
||
127 |
100% |
55.054 |
2023-04-28 |
1A.algo - la plus grande sous-séquence croissante - correction |
True |
59.179 |
10 |
10 |
10 |
|
128 |
87% |
3.295 |
2023-04-28 |
True |
7.381 |
8 |
7 |
7 |
||
129 |
100% |
4.924 |
2023-04-28 |
True |
9.053 |
10 |
10 |
10 |
||
130 |
100% |
1.827 |
2023-04-28 |
True |
5.962 |
6 |
6 |
6 |
||
131 |
100% |
19.052 |
2023-04-28 |
True |
23.180 |
8 |
8 |
8 |
||
132 |
100% |
0.131 |
2023-04-28 |
True |
4.229 |
7 |
7 |
7 |
||
133 |
100% |
1.579 |
2023-04-28 |
1A.data - Décorrélation de variables aléatoires - correction |
True |
5.744 |
15 |
15 |
15 |
|
134 |
100% |
8.138 |
2023-04-28 |
True |
12.407 |
51 |
51 |
51 |
||
135 |
100% |
24.011 |
2023-04-24 |
True |
28.092 |
22 |
22 |
22 |
||
136 |
100% |
13.504 |
2023-04-24 |
True |
17.806 |
9 |
9 |
9 |
||
137 |
87% |
102.569 |
2023-04-24 |
True |
106.978 |
16 |
14 |
14 |
||
138 |
100% |
8.116 |
2023-04-24 |
True |
12.560 |
18 |
18 |
18 |
||
139 |
100% |
189.773 |
2023-04-24 |
True |
193.936 |
14 |
14 |
14 |
||
140 |
100% |
31.360 |
2023-04-28 |
True |
35.583 |
23 |
23 |
23 |
||
141 |
100% |
93.308 |
2023-04-28 |
True |
97.584 |
33 |
33 |
33 |
||
142 |
100% |
3.051 |
2023-04-28 |
True |
7.243 |
15 |
15 |
15 |
||
143 |
100% |
30.841 |
2023-04-28 |
True |
35.366 |
15 |
15 |
15 |
||
144 |
100% |
9.290 |
2023-04-28 |
True |
13.704 |
45 |
45 |
45 |
||
145 |
100% |
41.301 |
2023-04-28 |
True |
45.882 |
35 |
35 |
35 |
||
146 |
100% |
3.133 |
2023-04-28 |
True |
7.248 |
11 |
11 |
11 |
||
147 |
100% |
36.788 |
2023-04-28 |
True |
41.060 |
64 |
64 |
64 |
||
148 |
100% |
50.301 |
2023-04-28 |
True |
54.491 |
18 |
18 |
18 |
||
149 |
100% |
1.041 |
2023-04-28 |
True |
5.198 |
14 |
14 |
14 |
||
150 |
100% |
17.008 |
2023-04-28 |
True |
21.211 |
28 |
28 |
28 |
||
151 |
100% |
5.262 |
2023-04-28 |
True |
9.553 |
24 |
24 |
24 |
||
152 |
100% |
25.142 |
2023-04-28 |
True |
29.318 |
16 |
16 |
16 |
||
153 |
100% |
60.299 |
2023-04-28 |
True |
64.490 |
32 |
32 |
32 |
||
154 |
100% |
12.991 |
2023-04-28 |
True |
17.177 |
14 |
14 |
14 |
||
155 |
100% |
40.120 |
2023-04-28 |
True |
44.464 |
19 |
19 |
19 |
||
156 |
100% |
60.137 |
2023-04-28 |
True |
64.341 |
24 |
24 |
24 |
||
157 |
100% |
2.277 |
2023-04-28 |
Distance entre deux mots de même longueur et tests unitaires |
True |
6.750 |
17 |
17 |
17 |
|
158 |
100% |
12.012 |
2023-04-28 |
True |
16.556 |
22 |
22 |
22 |
||
159 |
100% |
12.577 |
2023-04-28 |
True |
17.117 |
9 |
9 |
9 |
||
160 |
100% |
1.062 |
2023-04-28 |
True |
5.375 |
10 |
10 |
10 |
||
161 |
100% |
29.856 |
2023-04-28 |
True |
34.131 |
16 |
16 |
16 |
||
162 |
100% |
13.177 |
2023-04-28 |
True |
17.382 |
17 |
17 |
17 |
||
163 |
100% |
12.495 |
2023-04-28 |
True |
16.646 |
15 |
15 |
15 |
||
164 |
100% |
1.206 |
2023-04-28 |
True |
5.413 |
14 |
14 |
14 |
||
165 |
100% |
7.484 |
2023-04-28 |
True |
11.683 |
15 |
15 |
15 |
||
166 |
100% |
8.517 |
2023-04-28 |
True |
12.653 |
8 |
8 |
8 |
||
167 |
100% |
260.468 |
2023-04-28 |
True |
264.777 |
34 |
34 |
34 |
||
168 |
100% |
222.129 |
2023-04-28 |
True |
226.265 |
15 |
15 |
15 |
||
169 |
100% |
15.008 |
2023-04-28 |
True |
19.162 |
14 |
14 |
14 |
||
170 |
100% |
4.284 |
2023-04-28 |
True |
8.337 |
9 |
9 |
9 |
||
171 |
100% |
30.950 |
2023-04-28 |
True |
35.060 |
38 |
38 |
38 |
||
172 |
100% |
3.245 |
2023-04-28 |
True |
7.449 |
8 |
8 |
8 |
||
173 |
100% |
4.944 |
2023-04-28 |
True |
9.007 |
19 |
19 |
19 |
||
174 |
100% |
0.138 |
2023-04-28 |
True |
4.219 |
8 |
8 |
8 |
||
175 |
96% |
117.544 |
2023-04-24 |
True |
121.929 |
75 |
72 |
72 |
||
176 |
100% |
14.443 |
2023-04-28 |
True |
18.780 |
71 |
71 |
71 |
||
177 |
100% |
0.385 |
2023-04-28 |
True |
4.477 |
5 |
5 |
5 |
||
178 |
0% |
nan |
nan |
72 |
0 |
|||||
179 |
0% |
nan |
nan |
7 |
0 |
|||||
180 |
100% |
1.870 |
2023-04-28 |
True |
5.947 |
8 |
8 |
8 |
||
181 |
100% |
2.867 |
2023-04-24 |
2A.i - Modèle relationnel, analyse d’incidents dans le transport aérien |
True |
6.958 |
20 |
20 |
20 |
|
182 |
100% |
20.753 |
2023-04-24 |
td2a/td2a_cenonce_session_5_donnees_non_structurees_et_programmation_fonctionnelle.ipynb |
2A.i - Données non structurées et programmation fonctionnelle |
True |
24.870 |
30 |
30 |
30 |
183 |
96% |
67.089 |
2023-04-24 |
True |
71.182 |
27 |
26 |
26 |
||
184 |
100% |
8.829 |
2023-04-24 |
True |
12.923 |
13 |
13 |
13 |
||
185 |
100% |
5.110 |
2023-04-24 |
True |
9.208 |
6 |
6 |
6 |
||
186 |
100% |
38.234 |
2023-04-24 |
True |
42.343 |
24 |
24 |
24 |
||
187 |
100% |
1.548 |
2023-04-24 |
2A.i - Modèle relationnel, analyse d’incidents dans le transport aérien - correction |
True |
5.548 |
3 |
3 |
3 |
|
188 |
100% |
81.252 |
2023-04-24 |
td2a/td2a_correction_session_5_donnees_non_structurees_et_programmation_fonctionnelle_corrige.ipynb |
2A.i - Données non structurées, programmation fonctionnelle - correction |
True |
85.427 |
33 |
33 |
33 |
189 |
100% |
12.861 |
2023-04-24 |
True |
16.925 |
18 |
18 |
18 |
||
190 |
100% |
34.962 |
2023-04-24 |
2A.ml - Classification binaire avec features textuelles - correction |
True |
39.088 |
23 |
23 |
23 |
|
191 |
100% |
14.526 |
2023-04-28 |
True |
19.243 |
6 |
6 |
6 |
||
192 |
100% |
54.397 |
2023-04-28 |
True |
58.605 |
36 |
36 |
36 |
||
193 |
90% |
178.874 |
2023-04-28 |
True |
183.310 |
42 |
38 |
38 |
||
194 |
100% |
0.139 |
2023-04-28 |
True |
4.239 |
6 |
6 |
6 |
||
195 |
100% |
0.139 |
2023-04-28 |
True |
4.299 |
6 |
6 |
6 |
||
196 |
100% |
8.668 |
2023-04-28 |
True |
12.758 |
8 |
8 |
8 |
||
197 |
100% |
516.790 |
2023-04-28 |
2A.algo - Plus proches voisins en grande dimension - correction |
True |
520.937 |
20 |
20 |
20 |
|
198 |
100% |
0.202 |
2023-04-28 |
True |
4.338 |
6 |
6 |
6 |
||
199 |
100% |
0.150 |
2023-04-28 |
True |
4.224 |
5 |
5 |
5 |
||
200 |
100% |
0.586 |
2023-04-28 |
True |
4.706 |
6 |
6 |
6 |
||
201 |
100% |
0.133 |
2023-04-28 |
True |
4.307 |
6 |
6 |
6 |
||
202 |
100% |
24.596 |
2023-04-24 |
True |
28.685 |
29 |
29 |
29 |
||
203 |
100% |
24.727 |
2023-04-24 |
True |
29.027 |
6 |
6 |
6 |
||
204 |
100% |
4.386 |
2023-04-24 |
True |
8.584 |
11 |
11 |
11 |
||
205 |
100% |
89.622 |
2023-04-24 |
True |
93.974 |
32 |
32 |
32 |
||
206 |
100% |
2.260 |
2023-04-28 |
True |
6.420 |
14 |
14 |
14 |
||
207 |
100% |
10.539 |
2023-04-28 |
True |
14.681 |
15 |
15 |
15 |
||
208 |
100% |
4.124 |
2023-04-28 |
2A.eco - Rappel de ce que vous savez déjà mais avez peut-être oublié |
True |
8.267 |
29 |
29 |
29 |
|
209 |
100% |
17.410 |
2023-04-28 |
td2a_eco/td2a_TD5_Traitement_automatique_des_langues_en_Python.ipynb |
True |
21.600 |
34 |
34 |
34 |
|
210 |
100% |
33.822 |
2023-04-28 |
td2a_eco/td2a_TD5_Traitement_automatique_des_langues_en_Python_correction.ipynb |
2A.eco - Traitement automatique de la langue en Python - correction |
True |
38.111 |
35 |
35 |
35 |
211 |
100% |
0.000 |
2023-04-28 |
True |
4.041 |
1 |
1 |
1 |
||
212 |
100% |
1.512 |
2023-04-28 |
td2a_eco/td2a_eco_exercices_de_manipulation_de_donnees.ipynb |
2A.eco - Mise en pratique des séances 1 et 2 - Utilisation de pandas et visualisation |
True |
5.601 |
3 |
3 |
3 |
213 |
100% |
4.503 |
2023-04-28 |
td2a_eco/td2a_eco_exercices_de_manipulation_de_donnees_correction_a.ipynb |
2A.eco - Mise en pratique des séances 1 et 2 - Utilisation de pandas et visualisation - correction |
True |
8.602 |
10 |
10 |
10 |
214 |
100% |
7.835 |
2023-04-28 |
td2a_eco/td2a_eco_exercices_de_manipulation_de_donnees_correction_b.ipynb |
2A.eco - Mise en pratique des séances 1 et 2 - Utilisation de pandas et visualisation - correction |
True |
11.965 |
16 |
16 |
16 |
215 |
100% |
10.549 |
2023-04-28 |
td2a_eco/td2a_eco_exercices_de_manipulation_de_donnees_correction_c.ipynb |
2A.eco - Mise en pratique des séances 1 et 2 - Utilisation de pandas et visualisation - correction |
True |
14.663 |
14 |
14 |
14 |
216 |
100% |
46.289 |
2023-04-28 |
True |
50.390 |
12 |
12 |
12 |
||
217 |
100% |
4.298 |
2023-04-28 |
True |
8.458 |
26 |
26 |
26 |
||
218 |
100% |
5.504 |
2023-04-28 |
True |
9.713 |
36 |
36 |
36 |
||
219 |
100% |
35.119 |
2023-04-24 |
True |
39.232 |
29 |
29 |
29 |
||
220 |
100% |
53.528 |
2023-04-24 |
True |
58.121 |
29 |
29 |
29 |
||
221 |
0% |
nan |
td2a_eco2/td2a_eco_5d_Travailler_du_texte_les_expressions_regulieres.ipynb |
nan |
26 |
0 |
||||
222 |
0% |
nan |
td2a_eco2/td2a_eco_5d_Travailler_du_texte_les_expressions_regulieres_correction.ipynb |
2A.eco - Les expressions régulières : à quoi ça sert ? (correction) |
nan |
27 |
0 |
|||
223 |
100% |
57.852 |
2023-04-24 |
td2a_eco2/td2a_eco_NLP_tf_idf_ngrams_LDA_word2vec_sur_des_extraits_litteraires.ipynb |
True |
62.146 |
69 |
69 |
69 |
|
224 |
100% |
2170.049 |
2023-04-28 |
True |
2174.425 |
37 |
37 |
37 |
||
225 |
100% |
747.070 |
2023-04-24 |
True |
751.164 |
28 |
28 |
28 |
||
226 |
100% |
265.349 |
2023-04-28 |
True |
270.202 |
22 |
22 |
22 |
||
227 |
100% |
21.967 |
2023-04-28 |
True |
26.274 |
41 |
41 |
41 |
||
228 |
100% |
0.359 |
2023-04-28 |
2A.ml - Boosting, random forest, gradient - les features qu’ils aiment |
True |
4.491 |
4 |
4 |
4 |
|
229 |
100% |
10.539 |
2023-04-28 |
True |
14.693 |
27 |
27 |
27 |
||
230 |
100% |
165.323 |
2023-04-28 |
Hyperparamètres, LassoRandomForestRregressor et grid_search (correction) |
True |
169.464 |
15 |
15 |
15 |
|
231 |
100% |
4.402 |
2023-04-28 |
Hyperparamètres, LassoRandomForestRregressor et grid_search (énoncé) |
True |
8.675 |
4 |
4 |
4 |
|
232 |
100% |
2.713 |
2023-04-28 |
True |
6.880 |
12 |
12 |
12 |
||
233 |
100% |
19.721 |
2023-04-28 |
Rappels sur scikit-learn et le machine learning (correction) |
True |
23.931 |
21 |
21 |
21 |
|
234 |
100% |
36.474 |
2023-04-28 |
True |
40.853 |
42 |
42 |
42 |
||
235 |
100% |
103.544 |
2023-04-24 |
True |
109.367 |
18 |
18 |
18 |
||
236 |
100% |
187.698 |
2023-04-24 |
True |
192.197 |
16 |
16 |
16 |
||
237 |
100% |
3.948 |
2023-04-28 |
True |
8.071 |
9 |
9 |
9 |
||
238 |
100% |
4.775 |
2023-04-28 |
True |
8.894 |
6 |
6 |
6 |
||
239 |
100% |
59.834 |
2023-04-28 |
True |
64.007 |
25 |
25 |
25 |
||
240 |
100% |
51.659 |
2023-04-28 |
2A.data - Classification, régression, anomalies - correction |
True |
55.831 |
33 |
33 |
33 |
|
241 |
100% |
1736.394 |
2023-04-24 |
2A.ml - Statistiques descriptives avec scikit-learn - correction |
True |
1740.748 |
24 |
24 |
24 |
|
242 |
100% |
544.861 |
2023-04-24 |
True |
549.248 |
26 |
26 |
26 |
||
243 |
100% |
45.122 |
2023-04-28 |
True |
49.318 |
26 |
26 |
26 |
||
244 |
100% |
5.831 |
2023-04-28 |
True |
9.916 |
9 |
9 |
9 |
||
245 |
96% |
18.384 |
2023-04-24 |
True |
22.547 |
31 |
30 |
30 |
||
246 |
100% |
0.116 |
2023-04-24 |
True |
4.139 |
2 |
2 |
2 |
||
247 |
100% |
40.451 |
2023-04-28 |
2A.ml - Pipeline pour un réduction d’une forêt aléatoire - correction |
True |
44.573 |
24 |
24 |
24 |
|
248 |
100% |
6.782 |
2023-04-28 |
2A.ml - Pipeline pour un réduction d’une forêt aléatoire - énoncé |
True |
10.882 |
11 |
11 |
11 |
|
249 |
100% |
3.657 |
2023-04-28 |
True |
7.792 |
6 |
6 |
6 |
||
250 |
100% |
52.830 |
2023-04-28 |
True |
57.026 |
44 |
44 |
44 |
||
251 |
100% |
8.411 |
2023-04-28 |
True |
12.494 |
15 |
15 |
15 |
||
252 |
100% |
34.838 |
2023-04-28 |
True |
38.962 |
15 |
15 |
15 |
||
253 |
100% |
81.894 |
2023-04-28 |
True |
86.042 |
19 |
19 |
19 |
||
254 |
100% |
4.350 |
2023-04-28 |
True |
8.551 |
8 |
8 |
8 |