From 421baa3c50d2db935585e447a67fc3ddc4857494 Mon Sep 17 00:00:00 2001 From: eslopfer Date: Wed, 21 Dec 2022 15:22:43 +0000 Subject: [PATCH] docs(keras): fix audits format --- subjects/ai/keras/audit/README.md | 22 +++++++++++----------- 1 file changed, 11 insertions(+), 11 deletions(-) diff --git a/subjects/ai/keras/audit/README.md b/subjects/ai/keras/audit/README.md index ad983272..62c2dc72 100644 --- a/subjects/ai/keras/audit/README.md +++ b/subjects/ai/keras/audit/README.md @@ -1,6 +1,6 @@ #### 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` @@ -8,7 +8,7 @@ ###### Does it print `Python 3.x`? x >= 8 -##### Does `import jupyter`, `import numpy`, `import pandas`, and `import keras` run without any error ? +###### Does `import jupyter`, `import numpy`, `import pandas`, and `import keras` run without any error? --- @@ -16,7 +16,7 @@ #### Exercise 1: Sequential -##### The question 1 is validated if the output ends with `keras.engine.sequential.Sequential object at xxx` +###### For question 1, does the output end with `keras.engine.sequential.Sequential object at xxx`? --- @@ -24,9 +24,9 @@ #### Exercise 2: Dense -##### 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 fields `batch_input_shape`, `units` and `activation` match this output: +###### For question 1, do the fields `batch_input_shape`, `units` and `activation` match this output? ``` {'name': 'dense_7', @@ -46,7 +46,7 @@ 'bias_constraint': None} ``` -##### The question 2 is validated if the fields `units` and `activation` match this output: +###### For question 2, do the fields `units` and `activation` match this output? ``` {'name': 'dense_8', @@ -65,7 +65,7 @@ 'bias_constraint': None} ``` -##### The question 3 is validated if the fields `units` and `activation` match this output: +###### For question 3, do the fields `units` and `activation` match this output? ``` {'name': 'dense_9', @@ -90,7 +90,7 @@ #### Exercise 3: Architecture -##### The question 1 is validated if the code that creates the neural network is: +###### For question 1, is code that creates the neural network the following? ``` model = keras.Sequential() @@ -108,7 +108,7 @@ The first two layers could use another activation function that sigmoid (eg: rel #### Exercise 4: Optimize -##### The question 1 is validated if the output of `model.get_config()['layers']` matches the fields `batch_input_shape`, `units` and `activation`. +###### For question 1, does the output of `model.get_config()['layers']` match the fields `batch_input_shape`, `units` and `activation`? ``` [{'class_name': 'InputLayer', @@ -165,8 +165,8 @@ The first two layers could use another activation function that sigmoid (eg: rel 'bias_constraint': None}}] ``` -You should notice that the neural network is struggling to learn. By luck the initialization of the weights might have led to an accuracy close of 90%. But when I trained the neural network, with `batch_size=300` on the data here is the ouptput of the last epoch (50): +You should notice that the neural network is struggling to learn. By luck the initialization of the weights might have led to an accuracy close of 90%. But when I trained the neural network, with `batch_size=300` on the data here is the output of the last epoch (50): `Epoch 50/50 2/2 [==============================] - 0s 1ms/step - loss: 0.6559 - accuracy: 0.6274` -##### The question 2 is validated if the the accuracy at epoch 50 is higher than 95%. +###### For question 2, is the the accuracy at epoch 50 higher than 95%?