LeCun will teach his NYU deep learning course again in the Spring of 2017.
Unresolvable The public record could not settle it.
Promise: Commitments to the person's or organisation's own future action, with something to deliver: was it delivered?
What would count as true or false
True: LeCun taught (as instructor or co-instructor) his NYU deep learning course (for example DS-GA 1008 or its equivalent) in the Spring 2017 semester. NYU course listings, the course website or syllabus, or recorded lectures dated Spring 2017 that name him as instructor would show this. Mostly true: the course ran in Spring 2017 with LeCun as an instructor, but under a slightly different title or number, or with substantial co-teaching. Mostly false: LeCun taught the course, but in a later semester (for example Fall 2017 or Spring 2018) and not in Spring 2017, or he gave only a few guest lectures in a Spring 2017 offering led by someone else. False: records show the course was not offered in Spring 2017, or that the Spring 2017 offering was taught by others without LeCun as an instructor.
Set before the research began.
Evidence (1)
-
E1 Yann LeCun’s Deep Learning Course Free From NYU I Programmer · 8 December 2020
“This is courtesy of the New York University's Center for Data Science or NYU CDS for short, where Yann LeCun taught the course last Spring under the code name DS-GA 1008.”
Reasoning
E1 is dated December 2020 and says LeCun taught DS-GA 1008 at NYU "last Spring". In context that most likely means Spring 2020, not Spring 2017. No evidence given names LeCun as instructor of a Spring 2017 offering, or shows who taught the course that semester. So the evidence does not settle the claim.
Cite this claim
Yann LeCun, “LeCun will teach his NYU deep learning course again in the Spring of 2017.” (said 28 July 2016). Verdict: unresolvable. Reliability API, claim c_0177956e46f0, method 0.1.0+c876030c, dataset release v1.1.2. https://epistacklabs.com/claims/c_0177956e46f0
This claim is in dataset release v1.1.2, with the same verdict.
Reply to this claim
Verdicts are made automatically; how verdicts are made.