Classificar texto em categorias com a API Natural Language avaliações

Vadym S. · Revisado há over 1 year

brenno_ e. · Revisado há over 1 year

Vitalik G. · Revisado há over 1 year

Matheus s. · Revisado há over 1 year

Ігор М. · Revisado há over 1 year

Yurii D. · Revisado há over 1 year

Jessa Mae S. · Revisado há over 1 year

Task 6 python script is not formated

Vitaly U. · Revisado há over 1 year

Ihor K. · Revisado há over 1 year

Roman R. · Revisado há over 1 year

Iryna V. · Revisado há over 1 year

providnui p. · Revisado há over 1 year

Oleh T. · Revisado há over 1 year

very nice.

Arcanjo G. · Revisado há over 1 year

I think, you know, that the second part, related to classify-text.py does not work need to install pip install google.cloud for python pip install --user google-cloud-bigquery==2.34.4 "shapely<2" google-cloud-storage google-cloud-language fix errors in classify-text.py insert Project ID but thanks anyway for the interesting challenge

BuYn M. · Revisado há over 1 year

Kritika G. · Revisado há over 1 year

Camilo P. · Revisado há over 1 year

Deepnita M. · Revisado há over 1 year

Bad formatted bigquery python script with some errors not working Script must be like: ``` # Import necessary libraries from google.cloud import storage, language, bigquery # Set up your GCS, NL, and BigQuery clients storage_client = storage.Client() nl_client = language.LanguageServiceClient() bq_client = bigquery.Client(project='qwiklabs-gcp-01-b8b997bbdb2b') # Define dataset and table dataset_ref = bq_client.dataset('news_classification_dataset') dataset = bigquery.Dataset(dataset_ref) table_ref = dataset.table('article_data') table = bq_client.get_table(table_ref) # Function to classify the text def classify_text(article): response = nl_client.classify_text( document=language.Document( content=article, type_=language.Document.Type.PLAIN_TEXT ) ) return response rows_for_bq = [] files = storage_client.bucket('qwiklabs-test-bucket-gsp063').list_blobs() print("Got article files from GCS, sending them to the NL API (this will take ~2 minutes)...") # Send files to the NL API and save the result to send to BigQuery for file in files: if file.name.endswith('txt'): article_text = file.download_as_bytes() nl_response = classify_text(article_text) if len(nl_response.categories) > 0: rows_for_bq.append((str(article_text), nl_response.categories[0].name, nl_response.categories[0].confidence)) print("Writing NL API article data to BigQuery...") # Write article text + category data to BQ errors = bq_client.insert_rows(table, rows_for_bq) assert errors == [] ```

OLEG M. · Revisado há over 1 year

семен И. · Revisado há over 1 year

Nickolay K. · Revisado há over 1 year

Denys V. · Revisado há over 1 year