Art and Science of Machine Learning

Reviewing Learning Curves

# On the Notebook instances page, click NEW INSTANCE. Select TensorFlow Enterprise and choose the latest version of TensorFlow Enterprise 2.3 (with LTS) > Without GPUs.
git clone https://github.com/GoogleCloudPlatform/training-data-analyst
training-data-analyst > courses > machine_learning > deepdive2 > art_and_science_of_ml > labs > learning_rate.ipynb.

Exporting data from BigQuery to Cloud Storage

# On the Notebook instances page, click NEW INSTANCE. Select TensorFlow Enterprise and choose the latest version of TensorFlow Enterprise 2.3 (with LTS) > Without GPUs.
git clone https://github.com/GoogleCloudPlatform/training-data-analyst
training-data-analyst > courses > machine_learning > deepdive2 > art_and_science_of_ml > labs and open export_data_from_bq_to_gcs.ipynb.

Performing Hyperparameter Tuning

# On the Notebook instances page, click NEW INSTANCE. Select TensorFlow Enterprise and choose the latest version of TensorFlow Enterprise 2.3 (with LTS) > Without GPUs.
git clone https://github.com/GoogleCloudPlatform/training-data-analyst
training-data-analyst > courses > machine_learning > deepdive2 > art_and_science_of_ml > labs and open hyperparameter_tuning.ipynb.

Building a DNN using the Keras Functional API

# On the Notebook instances page, click NEW INSTANCE. Select TensorFlow Enterprise and choose the latest version of TensorFlow Enterprise 2.3 (with LTS) > Without GPUs.
git clone https://github.com/GoogleCloudPlatform/training-data-analyst
training-data-analyst > courses > machine_learning > deepdive2 > art_and_science_of_ml > labs and open neural_network.ipynb.

Training Models at Scale with AI Platform

# On the Notebook instances page, click NEW INSTANCE. Select TensorFlow Enterprise and choose the latest version of TensorFlow Enterprise 2.3 (with LTS) > Without GPUs.
git clone https://github.com/GoogleCloudPlatform/training-data-analyst
training-data-analyst > courses > machine_learning > deepdive2 > art_and_science_of_ml > labs > training_models_at_scale.ipynb.

Introducing the Keras Functional API

# On the Notebook instances page, click NEW INSTANCE. Select TensorFlow Enterprise and choose the latest version of TensorFlow Enterprise 2.3 (with LTS) > Without GPUs.
git clone https://github.com/GoogleCloudPlatform/training-data-analyst
training-data-analyst > courses > machine_learning > deepdive2 > introduction_to_tensorflow > Labs and open 4_keras_functional_api.ipynb.