Prepare Data for ML APIs on Google Cloud: Challenge Lab Reviews

Khushi S. · Reviewed 23 дней ago

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

Pavan D. · Reviewed 23 дней ago

Yeison A. · Reviewed 23 дней ago

Kanchi M. · Reviewed 23 дней ago

Sindhu 2. · Reviewed 23 дней ago

Jyoti B. · Reviewed 23 дней ago

kimiko G. · Reviewed 23 дней ago

Rashmi S. · Reviewed 23 дней ago

Nikhil S. · Reviewed 23 дней ago

SIVA GANESH M. · Reviewed 23 дней ago

Hariharan R. · Reviewed 23 дней ago

Yustin Eduardo P. · Reviewed 23 дней ago

Shafat A. · Reviewed 23 дней ago

Trâm N. · Reviewed 23 дней ago

Yishang Z. · Reviewed 23 дней ago

Shirisha A. · Reviewed 23 дней ago

harry G. · Reviewed 23 дней ago

Vishnuram G. · Reviewed 23 дней ago

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. · Reviewed 23 дней ago

tidak ada kendala di lab ini

Resha R. · Reviewed 23 дней ago

Thulasi G. · Reviewed 23 дней ago

Olena L. · Reviewed 23 дней ago

Shivaansh G. · Reviewed 23 дней ago

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

Beshoy T. · Reviewed 23 дней ago

Jeet P. · Reviewed 23 дней ago