diff --git a/subjects/ai/linear-regression/audit/README.md b/subjects/ai/linear-regression/audit/README.md index b31b6366..c31b2fe0 100644 --- a/subjects/ai/linear-regression/audit/README.md +++ b/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`? --- ---