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Course Level Date Clip# Line Interlocutor Content
Oral Assessments Graduate 2019-08-16 4 16 T01 uh sure→ are you ready now↗≈
Oral Assessments Graduate 2019-08-16 4 17 S01 +≈ ⁎yea⁎
Oral Assessments Graduate 2019-08-16 4 18 UNK (0.3)
Oral Assessments Graduate 2019-08-16 4 19 T01 ok sure mhm
Oral Assessments Graduate 2019-08-16 4 20 UNK (1.6)
Oral Assessments Graduate 2019-08-16 4 21 S01 so (1.6) today I- I'm gonna introduce a term→
Oral Assessments Graduate 2019-08-16 4 22 S01 um actually it's a it's a xxx uh t- (0.4) it's a really
Oral Assessments Graduate 2019-08-16 4 23 S01 broad concept↘ (1.4) called (2.3) numerical→ (2.2)
Oral Assessments Graduate 2019-08-16 4 24 S01 optimization↘
Oral Assessments Graduate 2019-08-16 4 25 UNK (5.9)
Oral Assessments Graduate 2019-08-16 4 26 S01 hm xxx now we are learning the ∆imaging processing∆ and
Oral Assessments Graduate 2019-08-16 4 27 S01 ∆pathway definition∆ or (0.4) like (0.7) like the→ (0.8)
Oral Assessments Graduate 2019-08-16 4 28 S01 the (0.3) artificial intelligence↘
Oral Assessments Graduate 2019-08-16 4 29 UNK (.)
Oral Assessments Graduate 2019-08-16 4 30 S01 everything y- you're thinking about (.) about the
Oral Assessments Graduate 2019-08-16 4 31 S01 computer science will (1.0) like we will use the numerical
Oral Assessments Graduate 2019-08-16 4 32 S01 optomization↘ it's very important to computer science↘
Oral Assessments Graduate 2019-08-16 4 33 UNK (0.5)
Oral Assessments Graduate 2019-08-16 4 34 S01 and (0.8) so (0.9) what (0.7) what's the (.) like the the
Oral Assessments Graduate 2019-08-16 4 35 S01 function of this kind of method↗ (0.4) is that→ (1.0) for