Commit e35b50d5 authored by Florent Chatelain's avatar Florent Chatelain
Browse files

up readme + nb

parent 37297f6f
......@@ -67,16 +67,19 @@ videoconference to the class every monday from 15:45 to 17:45.
- ~~**read the lesson** ([slides](https://gricad-gitlab.univ-grenoble-alpes.fr/chatelaf/ml-sicom3a/-/blob/master/slides/4_discriminant_analysis.pdf) ) on generative models: discriminant analysis + naïve Bayes~~
- ~~prepare your questions for the course/lab session!~~
-->
##### Homework for **Monday, September 27**
- **read the lesson** ([slides](https://gricad-gitlab.univ-grenoble-alpes.fr/chatelaf/ml-sicom3a/-/blob/master/slides/4_discriminant_analysis.pdf) ) on generative models: discriminant analysis + naïve Bayes
- prepare your questions for the course/lab session!
-->
##### Lab1 instructions
- Lab1 is scheduled on Monday 20 (13:30 - Z102 Minatec for IMMAC+doctoral/erasmus students), and 15:45 - Z012 Minatec for EEH students)
- Statement is [here](https://gricad-gitlab.univ-grenoble-alpes.fr/chatelaf/ml-sicom3a/-/blob/master/labs/lab1_statement.md)
<!-- upload your lab 1 *short report* in the [chamilo assigment task](https://chamilo.grenoble-inp.fr/main/work/work_list.php?cidReq=PHELMA5PMSAST6&id_session=0&gidReq=0&gradebook=0&origin=&id=117582) (pdf file from your editor, or scanned pdf file of a handwritten paper;
- upload your lab 1 *short report* in the [chamilo assigment task](https://chamilo.grenoble-inp.fr/main/work/work_list.php?cidReq=PHELMA5PMSAST6&id_session=0&gidReq=0&gradebook=0&origin=&id=117582) (pdf file from your editor, or scanned pdf file of a handwritten paper;
code, figures or graphics are not required)
-->
##### Homework before the first lab on **Monday, September 20**
- read and run the [introduction notebooks](https://gricad-gitlab.univ-grenoble-alpes.fr/chatelaf/ml-sicom3a/-/tree/master/notebooks/1_introduction/) `N1_Linear_Classification.ipynb` and `N2_Polynomial_Classification_Model_Complexity.ipynb`
......
......@@ -10,11 +10,11 @@
import matplotlib
import numpy as np
import scipy as sp
import matplotlib.pyplot as plt
# Select random seed
random_state = 1
random_state = 0
```
%% Cell type:markdown id: tags:
# Model Complexity
......
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