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--min-cpu-platform=Intel\ Skylake

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export IMAGE_FAMILY="tf-latest-cpu" # or put any required
export ZONE="us-west1-b"
export INSTANCE_NAME="my-instance"
export INSTANCE_TYPE="n1-standard-8"
gcloud compute instances create $INSTANCE_NAME \
        --zone=$ZONE \
        --image-family=$IMAGE_FAMILY \
        --image-project=deeplearning-platform-release \
        --machine-type=$INSTANCE_TYPE \
        --boot-disk-size=120GB \

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export PROJECT_NAME="" # put your project name
export INSTANCE_NAME="" # put the instance name
# pick the zone that is supported by tpu:
# https://cloud.google.com/tpu/docs/regions
export ZONE="us-central1-b" 

gcloud compute instances create $INSTANCE_NAME \
  --project=$PROJECT_NAME \
  --zone=$ZONE \
  --machine-type=n1-standard-2 \

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gssh --zone $ZONE $INSTANCE_NAME -- -L 8080:localhost:8080

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import tensorflow as tf

TPU_WORKER = '10.0.101.2:8470' # put your IP!
session = tf.Session('grpc://' + TPU_WORKER,
                     config=tf.ConfigProto(isolate_session_state=True))

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export PROJECT_NAME="" # put your project name
export INSTANCE_NAME="" # put the instance name
# pick the zone that is supported by tpu:
# https://cloud.google.com/tpu/docs/regions
export ZONE="us-central1-b" 

gcloud compute instances create $INSTANCE_NAME \
  --project=$PROJECT_NAME \
  --zone=$ZONE \
  --machine-type=n1-standard-2 \

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export IMAGE_FAMILY="chainer-latest-cu92-experimental"
export ZONE="us-west1-b"
export INSTANCE_NAME="chainer-test"
gcloud compute instances create $INSTANCE_NAME \
        --zone=$ZONE \
        --image-family=$IMAGE_FAMILY \
        --image-project=deeplearning-platform-release \
        --maintenance-policy=TERMINATE \
        --accelerator='type=nvidia-tesla-v100,count=1' \
        --metadata='install-nvidia-driver=True'

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export IMAGE_FAMILY="common-cpu"
export ZONE="us-west1-b"
export INSTANCE_NAME="jupyter-with-custom-user"
gcloud compute instances create $INSTANCE_NAME \
        --zone=$ZONE \
        --image-family=$IMAGE_FAMILY \
        --image-project=deeplearning-platform-release \
        --metadata="jupyter-user=bob"

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%%bigquery
SELECT
    source_year AS year,
    COUNT(is_male) AS birth_count
FROM `bigquery-public-data.samples.natality`
GROUP BY year
ORDER BY year DESC
LIMIT 15

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import numpy as np
import tensorflow as tf
import pandas as pd

FEATURES = ["SqFt", "Bedrooms", "Offers"]
LABEL = "Price"

feature_cols = [tf.feature_column.numeric_column(k) for k in FEATURES]
estimator = tf.estimator.LinearRegressor(    
        feature_columns=feature_cols,