Analisar avaliações de clientes com o Gemini usando notebooks Python avaliações

Narayana M. · Revisado há about 1 year

good

sutrisno m. · Revisado há about 1 year

Indusara Darshana A. · Revisado há about 1 year

Utkarsh S. · Revisado há about 1 year

Nandi S. · Revisado há about 1 year

Prabhat G. · Revisado há about 1 year

Prabhat G. · Revisado há about 1 year

Prabhat G. · Revisado há about 1 year

Senthil K. · Revisado há about 1 year

Satyam K. · Revisado há about 1 year

Vinayak G. · Revisado há about 1 year

Omer B. · Revisado há about 1 year

lohau l. · Revisado há about 1 year

Abhijit G. · Revisado há about 1 year

"Create a Python notebook in BigQuery using Colab Enterprise. Create a Cloud Resource connection in BigQuery. Create the dataset and tables in BigQuery. Create the Gemini remote models in BigQuery. Prompt Gemini to analyze keywords and setiment (positive, or negative) for text based customer reviews. Generate a report with a count of positive, and negative reviews. Respond to customer reviews at scale. Create an application for customer service representatives to respond to audio based customer reviews."

Rehma I. · Revisado há about 1 year

CLOUD S. · Revisado há about 1 year

sathvika r. · Revisado há about 1 year

Siddharth G. · Revisado há about 1 year

just the connect alone already took more than 10 minutes to connect and the instructions didn't state which connect button as there's 2 connect buttons with top and bottom.

Wei Loon T. · Revisado há about 1 year

Pratham C. · Revisado há about 1 year

ANUJ R. · Revisado há about 1 year

Claudio C. · Revisado há about 1 year

Piyush J. · Revisado há about 1 year

Bibek C. · Revisado há about 1 year

Riya Y. · Revisado há about 1 year