AI Platform Training でのカスタム コンテナの使用 のレビュー

Lee Jiin · 4年弱前にレビュー済み

That took so long!

Dumas Pierre-Yves · 4年弱前にレビュー済み

Urrego Christian · 4年弱前にレビュー済み

Heikka Lauri · 4年弱前にレビュー済み

Roux Louis · 4年弱前にレビュー済み

Navarro Guerrero Gerardo · 4年弱前にレビュー済み

Young Jeric · 4年弱前にレビュー済み

Guimaraes Dziewulski Augusto · 4年弱前にレビュー済み

Time limit is too tight as this lab has relatively many coding tasks spanning across systems, and the long running time of training/tuning job (~10min) means that any coding error results in a need to rerun the job. This makes the margin of error pretty small (only chance for a few course correction before lab runs out of time). I optimized the setup/beginning portion of the lab by doing tasks in parallel, but even then it took me 1:30 (1 mistake: hypertune.Hypertune -> hypertune.HyperTune). This lab is execellent for making student experience how tedious it is to do AI end-to-end manually though. (which makes the need for good MLOps all the more convincing)

Lam Tom · 4年弱前にレビュー済み

Metwaly Zarad Ahmed · 4年弱前にレビュー済み

krishna vadlamudi sai · 4年弱前にレビュー済み

Pantovic Aleksandar · 4年弱前にレビュー済み

Instruction says use 80% data for training but the SQL only checked membership in 1,2,3,4 instead of 0,1,2,3,4,5,6,7? Also lacking explanation of what is --hptune and --nohptune. It's some magic variable not found in documentation

MLE Pro · 4年弱前にレビュー済み

PELLA TYSON OMBOK · 4年弱前にレビュー済み

I was getting errors when running the pipeline such as file not found. I didn't know what to do in that situation. If support was available I would have been able to get more out of the Lab. Other than that it was well designed.

Patel Yukta · 4年弱前にレビュー済み

LEONARDO FURIO · 4年弱前にレビュー済み

S Satoshi · 4年弱前にレビュー済み

Cufaro Tomas · 4年弱前にレビュー済み

Klebanov Alexander · 4年弱前にレビュー済み

Pais Helio · 4年弱前にレビュー済み

José Montiel Pérez external Victor · 4年弱前にレビュー済み

Nwiran Belal · 4年弱前にレビュー済み

Nabil Atwa Ahmed · 4年弱前にレビュー済み

Kösüre Engin · 4年弱前にレビュー済み

Too long...too much time to wait without nothing to do

rauch nadia · 4年弱前にレビュー済み