docs(linear-regression-with-scikit-learn): fix audits format

subjects/ai/linear-regression/audit/README.md

@@ -2,7 +2,7 @@
 
 #### Exercise 0: Environment and libraries
 
-##### The exercice is validated is all questions of the exercice are validated
+##### The exercise is validated is all questions of the exercise are validated
 
 ##### Activate the virtual environment. If you used `conda` run `conda activate your_env`
 
@@ -10,7 +10,7 @@
 
 ###### Does it print `Python 3.x`? x >= 8
 
-###### Does `import jupyter`, `import numpy`, `import pandas`, `import matplotlib` and `import sklearn` run without any error ?
+###### Do `import jupyter`, `import numpy`, `import pandas`, `import matplotlib` and `import sklearn` run without any error?
 
 ---
 
@@ -18,13 +18,13 @@
 
 #### Exercise 1: Scikit-learn estimator
 
-##### The question 1 is validated if the output is:
+###### For question 1, is the output the following?
 
 ```python
     array([[3.96013289]])
 ```
 
-##### The question 2 is validated if the output is:
+###### For question 2, is the output the following?
 
 ```output
     Coefficients:  [[0.99667774]]
@@ -38,23 +38,23 @@
 
 #### Exercise 2: Linear regression in 1D
 
-##### The exercise is validated is all questions of the exercise are validated
+##### The exercise is validated if all questions of the exercise are validated
 
-##### The question 1 is validated if the plot looks like:
+###### For question 1, does the plot look like the following?
 
 ![alt text][q1]
 
 [q1]: ../w2_day1_ex2_q1.png "Scatter plot"
 
-###### The question 2 is validated if the equation of the fitted line is: `y = 42.619430291366946 * x + 99.18581817296929`
+###### For question 2, is the equation of the fitted line the following? `y = 42.619430291366946 * x + 99.18581817296929`
 
-###### The question 3 is validated if the plot looks like:
+###### For question 3, does the plot look like the following?
 
 ![alt text][q3]
 
 [q3]: ../w2_day1_ex2_q3.png "Scatter plot + fitted line"
 
-###### The question 4 is validated if the outputted prediction for the first 10 values are:
+###### For question 4, is the outputted prediction for the first 10 values the following?
 
 ```python
 array([ 83.86186727, 140.80961751, 116.3333897 ,  64.52998689,
@@ -62,9 +62,9 @@ array([ 83.86186727, 140.80961751, 116.3333897 ,  64.52998689,
        108.06237908,  85.90762675])
 ```
 
-###### The question 5 is validated if the MSE returned is `114.17148616819485`
+###### For question 5, is the MSE returned `114.17148616819485`?
 
-###### The question 6 is validated if the MSE returned is `2854.2871542048706`
+###### For question 6, is the MSE returned `2854.2871542048706`?
 
 ---
 
@@ -72,7 +72,7 @@ array([ 83.86186727, 140.80961751, 116.3333897 ,  64.52998689,
 
 #### Exercise 3: Train test split
 
-##### The question 1 is validated if X_train, y_train, X_test, y_test match this output:
+###### For question 1, do X_train, y_train, X_test, y_test match this output?
 
 ```console
 X_train:
@@ -105,9 +105,9 @@ y_test:
 
 #### Exercise 4: Forecast diabetes progression
 
-##### The exercice is validated is all questions of the exercice are validated
+##### The exercise is validated if all questions of the exercise are validated
 
-##### The question 1 is validated if the output of `y_train.values[:10]` and `y_test.values[:10]`are:
+###### For question 1, is the output of `y_train.values[:10]` and `y_test.values[:10]` the following?
 
 ```console
     y_train.values[:10]:
@@ -135,7 +135,7 @@ y_test:
     [192.]]
 ```
 
-##### The question 2 is validated if the coefficients and the intercept are:
+###### For question 2, are the coefficients and the intercept the following?
 
 ```console
     [('age', -60.40163046086952),
@@ -151,7 +151,7 @@ y_test:
     ('intercept', 152.05314895029233)]
 ```
 
-##### The question 3 is validated if the output of `predictions_on_test[:10]` is:
+###### For question 3, is the output of `predictions_on_test[:10]`?
 
 ```console
     array([[111.74351759],
@@ -166,7 +166,7 @@ y_test:
         [224.83346984]])
 ```
 
-##### The question 4 is validated if the mse on the **train set** is `2888.326888` and the mse on the **test set** is `2858.255153`.
+###### For question 4, is the mse on the **train set** `2888.326888` and the mse on the **test set** `2858.255153`?
 
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