Expand alt text in episode 2

episodes/2-keras.Rmd

@@ -76,10 +76,10 @@
 The `palmerpenguins` data contains size measurements for three penguin species observed on three islands in the Palmer Archipelago, Antarctica.
 The physical attributes measured are flipper length, beak length, beak width, body mass, and sex.
 
 ![*Artwork by @allison_horst*][palmer-penguins]
 
 
 ![*Artwork by @allison_horst*][penguin-beaks]
 
 
 These data were collected from 2007 - 2009 by Dr. Kristen Gorman with the [Palmer Station Long Term Ecological Research Program](https://pal.lternet.edu/), part of the [US Long Term Ecological Research Network](https://lternet.edu/). The data were imported directly from the [Environmental Data Initiative](https://environmentaldatainitiative.org/) (EDI) Data Portal, and are available for use by CC0 license ("No Rights Reserved") in accordance with the [Palmer Station Data Policy](https://pal.lternet.edu/data/policies).
@@ -140,7 +140,7 @@
 sns.pairplot(penguins, hue="species")
 ```
 
-![][pairplot]
+![][pairplot]{alt='Grid of scatter plots and histograms comparing observed values of the four physicial attributes (variables) measured in the penguins sampled. Scatter plots illustrate the distribution of values observed for each pair of variables. On the diagonal, where one physical attribute would be compared with itself, histograms are displayed that show the distribution of values observed for that attibute, coloured according to the species of the individual sampled. The pair plot shows distinct but overlapping clusters of data points representing the different species, with no pair of variables providing a clean separation of clusters on its own.'}
 
 ::: challenge
 
@@ -165,7 +165,7 @@
 sns.pairplot(penguins, hue='sex')
 ```
 
-![][sex_pairplot]
+![][sex_pairplot]{alt='Grid of scatter plots and histograms comparing observed values of the four physicial attributes (variables) measured in the penguins sampled, with data points coloured according to the sex of the individual sampled. The pair plot shows similarly-shaped distribution of values observed for each variable in male and female penguins, with the distribution of measurements for females skewed towards smaller values.'}
 
 You see that for each species females have smaller bills and flippers, as well as a smaller body mass.
 You would need a combination of the species and the numerical features to successfully distinguish males from females.
@@ -526,7 +526,7 @@
 ```python
 sns.lineplot(x=history.epoch, y=history.history['loss'])
 ```
 ![][training_curve]
 
 This plot can be used to identify whether the training is well configured or whether there
 are problems that need to be addressed.
@@ -545,7 +545,7 @@
 
 3. (optional) Something went wrong here during training. What could be the problem, and how do you see that in the training curve?
 Also compare the range on the y-axis with the previous training curve.
-![](../fig/02_bad_training_history_1.png){alt='Very jittery training curve with the loss value jumping back and forth between 2 and 4. The range of the y-axis is from 2 to 4, whereas in the previous training curve it was from 0 to 2. The loss seems to decrease a litle bit, but not as much as compared to the previous plot where it dropped to almost 0. The minimum loss in the end is somewhere around 2.'}
+![][bad-training-curve]
 
 :::: solution
 ## Solution
@@ -686,7 +686,7 @@
 ```python
 sns.heatmap(confusion_df, annot=True)
 ```
 ![][confusion_matrix]
 
 ::: challenge
 ## Confusion Matrix
@@ -771,17 +771,20 @@
 {alt='Illustration of the three species of penguins found in the Palmer Archipelago, Antarctica: Chinstrap, Gentoo and Adele'}
 
 [penguin-beaks]: fig/culmen_depth.png "Culmen Depth"
-{alt='Illustration of the beak dimensions called culmen length and culmen depth in the dataset'}
+{alt='Illustration of how the beak dimensions were measured. In the raw data, bill dimensions are recorded as "culmen length" and "culmen depth". The culmen is the dorsal ridge atop the bill.'}
 
 [pairplot]: fig/pairplot.png "Pair Plot"
-{alt='Pair plot showing the separability of the three species of penguin for combinations of dataset attributes'}
+{alt='Grid of scatter plots and histograms comparing observed values of the four physicial attributes (variables) measured in the penguins sampled. Scatter plots illustrate the distribution of values observed for each pair of variables. On the diagonal, where one physical attribute would be compared with itself, histograms are displayed that show the distribution of values observed for that attibute, coloured according to the species of the individual sampled. The pair plot shows distinct but overlapping clusters of data points representing the different species, with no pair of variables providing a clean separation of clusters on its own.'}
 
 [sex_pairplot]: fig/02_sex_pairplot.png "Pair plot grouped by sex"
-{alt='Pair plot showing the separability of the two sexes of penguin for combinations of dataset attributes'}
+{alt='Grid of scatter plots and histograms comparing observed values of the four physicial attributes (variables) measured in the penguins sampled, with data points coloured according to the sex of the individual sampled. The pair plot shows similarly-shaped distribution of values observed for each variable in male and female penguins, with the distribution of measurements for females skewed towards smaller values.'}
 
 [training_curve]: fig/02_training_curve.png "Training Curve"
 {alt='Training loss curve of the neural network training which depicts exponential decrease in loss before a plateau from ~10 epochs'}
 
+[bad-training-curve]: ../fig/02_bad_training_history_1.png "Training Curve Gone Wrong"
+{alt='Very jittery training curve with the loss value jumping back and forth between 2 and 4. The range of the y-axis is from 2 to 4, whereas in the previous training curve it was from 0 to 2. The loss seems to decrease a litle bit, but not as much as compared to the previous plot where it dropped to almost 0. The minimum loss in the end is somewhere around 2.'}
+
 [confusion_matrix]: fig/confusion_matrix.png "Confusion Matrix"
 {alt='Confusion matrix of the test set with high accuracy for Adelie and Gentoo classification and no correctly predicted Chinstrap'}