关于“在 Google Cloud 上为机器学习 API 准备数据：实验室挑战赛”的评价

Khushi S. · 已于 22 days前审核

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

Pavan D. · 已于 23 days前审核

Yeison A. · 已于 23 days前审核

Kanchi M. · 已于 23 days前审核

Sindhu 2. · 已于 23 days前审核

Jyoti B. · 已于 23 days前审核

kimiko G. · 已于 23 days前审核

Rashmi S. · 已于 23 days前审核

Nikhil S. · 已于 23 days前审核

SIVA GANESH M. · 已于 23 days前审核

Hariharan R. · 已于 23 days前审核

Yustin Eduardo P. · 已于 23 days前审核

Shafat A. · 已于 23 days前审核

Trâm N. · 已于 23 days前审核

Yishang Z. · 已于 23 days前审核

Shirisha A. · 已于 23 days前审核

harry G. · 已于 23 days前审核

Vishnuram G. · 已于 23 days前审核

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. · 已于 23 days前审核

tidak ada kendala di lab ini

Resha R. · 已于 23 days前审核

Thulasi G. · 已于 23 days前审核

Olena L. · 已于 23 days前审核

Shivaansh G. · 已于 23 days前审核

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

Beshoy T. · 已于 23 days前审核

Jeet P. · 已于 23 days前审核