End-to-End Machine Learning with TensorFlow on GCP

Explore dataset

# On the Notebook instances page, click NEW INSTANCE. Select TensorFlow Enterprise and choose the latest version of TensorFlow Enterprise 2.6 (with LTS) > Without GPUs.
git clone https://github.com/GoogleCloudPlatform/training-data-analyst
training-data-analyst > courses > machine_learning > deepdive > 06_structured and open 1_explore.ipynb.

Create a sample dataset

# On the Notebook instances page, click NEW INSTANCE. Select TensorFlow Enterprise and choose the latest version of TensorFlow Enterprise 2.6 (with LTS) > Without GPUs.
git clone https://github.com/GoogleCloudPlatform/training-data-analyst
training-data-analyst > courses > machine_learning > deepdive2 > end_to_end_ml > labs and open sample_babyweight.ipynb.

Create TensorFlow model - Creating Keras DNN model

# On the Notebook instances page, click NEW INSTANCE. Select TensorFlow Enterprise and choose the latest version of TensorFlow Enterprise 2.6 (with LTS) > Without GPUs.
git clone https://github.com/GoogleCloudPlatform/training-data-analyst
training-data-analyst > courses > machine_learning > deepdive2 > end_to_end_ml > labs and open keras_dnn_babyweight.ipynb.

Preprocessing using Cloud Dataflow - Preprocessing using a Dataflow

# Create Storage Bucket
# On the Notebook instances page, click NEW INSTANCE. Select TensorFlow Enterprise and choose the latest version of TensorFlow Enterprise 2.6 (with LTS) > Without GPUs.
git clone https://github.com/GoogleCloudPlatform/training-data-analyst
training-data-analyst > courses > machine_learning > deepdive2 > end_to_end_ml > labs and open preproc.ipynb.

Training on Cloud AI Platform - Training on Cloud AI Platform

# Create Storage Bucket
# On the Notebook instances page, click NEW INSTANCE. Select TensorFlow Enterprise and choose the latest version of TensorFlow Enterprise 2.6 (with LTS) > Without GPUs.
git clone https://github.com/GoogleCloudPlatform/training-data-analyst
training-data-analyst > courses > machine_learning > deepdive > 06_structured and open 5_train.ipynb.

Deploying and predicting with Cloud AI Platform - Deploying and predicting with Cloud AI Platform

# Create Storage Bucket
# On the Notebook instances page, click NEW INSTANCE. Select TensorFlow Enterprise and choose the latest version of TensorFlow Enterprise 2.6 (with LTS) > Without GPUs.
git clone https://github.com/GoogleCloudPlatform/training-data-analyst
training-data-analyst > courses > machine_learning > deepdive2 > end_to_end_ml > labs and open deploy_keras_ai_platform_babyweight.ipynb.