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

Khushi S. · Examiné il y a 23 jours

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

Pavan D. · Examiné il y a 23 jours

Yeison A. · Examiné il y a 23 jours

Kanchi M. · Examiné il y a 23 jours

Sindhu 2. · Examiné il y a 23 jours

Jyoti B. · Examiné il y a 23 jours

kimiko G. · Examiné il y a 23 jours

Rashmi S. · Examiné il y a 23 jours

Nikhil S. · Examiné il y a 23 jours

SIVA GANESH M. · Examiné il y a 23 jours

Hariharan R. · Examiné il y a 23 jours

Yustin Eduardo P. · Examiné il y a 23 jours

Shafat A. · Examiné il y a 23 jours

Trâm N. · Examiné il y a 23 jours

Yishang Z. · Examiné il y a 23 jours

Shirisha A. · Examiné il y a 23 jours

harry G. · Examiné il y a 23 jours

Vishnuram G. · Examiné il y a 23 jours

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. · Examiné il y a 23 jours

tidak ada kendala di lab ini

Resha R. · Examiné il y a 23 jours

Thulasi G. · Examiné il y a 23 jours

Olena L. · Examiné il y a 23 jours

Shivaansh G. · Examiné il y a 23 jours

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

Beshoy T. · Examiné il y a 23 jours

Jeet P. · Examiné il y a 23 jours