Create ML Models with BigQuery ML: Challenge Lab转至实验
Great lab content but scoring system errors ruins the experience. To pass task 5 you have to use literally the name of the busiest station and use literally the name of the average value. If you use a nested query to find the busiest station or use a variable name different to the one the scoring system is expecting, you do not pass the score. Also the scoring system does not takes into account the fact that there are different spellings for Single Trip and the station names in the 2019 and 2018 datasets. I could pass it thanks to the always helpful support team.
The definition of "busiest station" in task 5 is ambiguous.
last task: busiest station is ambiguous as start_station_id to start_station_name is not 1:1, could mean busiest station_id, busiest stations name, busiest loc with respect to SingleTrip; pay as you ride could be counted as single trip -lots of options here
The task description does not always appear to be clear and detailled enough which makes this artificially difficult to resolve :-(
last task has issues. tried all solutions. Checked with support person and they also found the answer is correct but system is not accepting. worst experience.
I could not get past Task 4 for some strange error message like 'Failed to update assessment result' - waited for more than half an hour in a chat just to find out the issue has to be raised with the testing team. For me thats just another bad experience with this learning platform in a row with many other very similar examples :-(