June 22, 2025
Class 9.1: Transfer Learning Example
"The cost in the made-up dataset
is dependent on the species, so the previous learning should be helpful."
To verify:
https://claude.ai
Enter "what is the average cost of each species?"
and upload iris_cost.csv.
Response:
Based on the analysis of your iris cost data, here are the average costs for each species:
Average Cost by Species:
Setosa: $2.24 (77 samples)
Range: $1.23 - $4.54
Versicolor: $4.85 (75 samples)
Range: $1.54 - $8.70
Virginica: $7.26 (98 samples)
Range: $2.50 - $13.89
June 27, 2025
What does train_ds.take(2) do?
train_ds is one of the return values of
(train_ds, val_ds, test_ds), metadata = tfds.load(
'tf_flowers',
data_dir=DATA_PATH,
split=['train[:80%]', 'train[80%:90%]', 'train[90%:]'],
with_info=True,
as_supervised=True,
)
Process of loading datasets
On the Overview page
https://www.tensorflow.org/datasets/api_docs/python/tfds
there is a link to a Colab tutorial:
https://colab.research.google.com/github/tensorflow/datasets/blob/master/docs/overview.ipynb
In the section "Load a dataset":
tfds.load() will download the data and save it as tfrecord files.
For example, if we set the parameter data_dir to
tfds.load(
'mnist',
data_dir="local_data/tfds",
the directory local_data/tfds/mnist/3.0.1 will contain the files
dataset_info.json
features.json
image.image.json
mnist-test.tfrecord-00000-of-00001
mnist-train.tfrecord-00000-of-00001
TFRecord and tf.train.Example
https://www.tensorflow.org/tutorials/load_data/tfrecord
