Preparação de dados para APIs de ML no Google Cloud: laboratório com desafio avaliações

The instruction are not clear. Copying the result files to the set location was not easy to figure out.

Pavan D. · Revisado há 23 days

Yeison A. · Revisado há 23 days

Kanchi M. · Revisado há 23 days

Sindhu 2. · Revisado há 23 days

Jyoti B. · Revisado há 23 days

kimiko G. · Revisado há 23 days

Rashmi S. · Revisado há 23 days

Nikhil S. · Revisado há 23 days

SIVA GANESH M. · Revisado há 23 days

Hariharan R. · Revisado há 23 days

Yustin Eduardo P. · Revisado há 23 days

Shafat A. · Revisado há 23 days

Trâm N. · Revisado há 23 days

Yishang Z. · Revisado há 23 days

Shirisha A. · Revisado há 23 days

harry G. · Revisado há 23 days

Vishnuram G. · Revisado há 23 days

A solid, practical module covering how to prepare and format data appropriately for consumption by Google Cloud's Machine Learning APIs, likely touching on data cleaning, formatting requirements, and preprocessing steps specific to different API types (Vision, Speech, Natural Language, etc.). It walks through key concepts around ensuring data quality and compatibility before sending it to ML APIs, which is a foundational but often overlooked step in building reliable ML-powered applications. The hands-on approach helps reinforce best practices for data preprocessing across different API contexts. Some prior familiarity with basic data handling and Google Cloud ML APIs is helpful for smoother comprehension. Overall, a useful module for building foundational data preparation skills for ML integration on Google Cloud.

Beny C. · Revisado há 23 days

tidak ada kendala di lab ini

Resha R. · Revisado há 23 days

Thulasi G. · Revisado há 23 days

Olena L. · Revisado há 23 days

Shivaansh G. · Revisado há 23 days

lab fails on task 2 when us=central1 is the specified version

Beshoy T. · Revisado há 23 days

Jeet P. · Revisado há 23 days

Nice!

Ni Komang Tri Buana D. · Revisado há 23 days