Google Cloud에서 기초 데이터, ML, AI 작업 수행: Challenge Lab

bq mk lab

gsutil cp gs://cloud-training/gsp323/lab.csv .

cat lab.csv

gsutil cp gs://cloud-training/gsp323/lab.schema .

cat lab.schema

gs://cloud-training/gsp323/runs.csv structure:

Note: Your Dataprep job should look similar to the following

Make sure you run the job. You will need to wait until the Dataflow job completes before you can grade this task.

gcloud iam service-accounts create my-natlang-sa \
  --display-name "my natural language service account"

gcloud iam service-accounts keys create ~/key.json \
  --iam-account my-natlang-sa@${GOOGLE_CLOUD_PROJECT}.iam.gserviceaccount.com

export GOOGLE_APPLICATION_CREDENTIALS="/home/$USER/key.json"

gcloud auth activate-service-account my-natlang-sa@${GOOGLE_CLOUD_PROJECT}.iam.gserviceaccount.com --key-file=$GOOGLE_APPLICATION_CREDENTIALS

gcloud ml language analyze-entities --content="Old Norse texts portray Odin as one-eyed and long-bearded, frequently wielding a spear named Gungnir and wearing a cloak and a broad hat." > result.json

gcloud auth login
(Copy the token from the link provided)


gsutil cp result.json gs://YOUR_PROJECT-marking/task4-cnl.result

export API_KEY={Replace with API KEY}

nano request.json

{
  "config": {
      "encoding":"FLAC",
      "languageCode": "en-US"
  },
  "audio": {
      "uri":"gs://cloud-training/gsp323/task4.flac"
  }
}

curl -s -X POST -H "Content-Type: application/json" --data-binary @request.json \
"https://speech.googleapis.com/v1/speech:recognize?key=${API_KEY}" > result.json

gsutil cp result.json gs://YOUR_PROJECT-marking/task4-gcs.result


gcloud iam service-accounts create quickstart

gcloud iam service-accounts keys create key.json --iam-account quickstart@${GOOGLE_CLOUD_PROJECT}.iam.gserviceaccount.com

gcloud auth activate-service-account --key-file key.json

export ACCESS_TOKEN=$(gcloud auth print-access-token)


nano request.json