How is everyone preparing and feeling for the HSC? (1 Viewer)

[splatcat]

Wait i thought most ppl were doing it on their own laptops im kinda thankful because i would make SO MANY typos if i was on another computer

Are chargers allowed in the exam, they aren't on the equipment list

 

[Socialism]

How are we feeling about the machine learning algorithms? I haven't done any revision yet and I've got no clue what k-nearest neighbour is

 

[splatcat]

How are we feeling about the machine learning algorithms? I haven't done any revision yet and I've got no clue what k-nearest neighbour is

knn is a supervised one where it classifies based on the classification of the k (arbitrary number) nearest neighbours. This can be used for both regression and classification. The other regressions are pretty simple and we don't need to implement or code them, just know when to use them

 

[emlr]

How are we feeling about the machine learning algorithms? I haven't done any revision yet and I've got no clue what k-nearest neighbour is

I think most of the ML algorithms are fine but like i have no clue on how Devops improves with ML

 

[splatcat]

Also surely they wouldn't ask for file handling with the python even if its in the course specs

 

[emlr]

Are chargers allowed in the exam, they aren't on the equipment list

I think so but im still going to fully charge my laptop just in case

 

[splatcat]

I think so but im still going to fully charge my laptop just in case

Exam is only 2:30 so most people should be fine, not sure how much the lockdown browser drains though

 

[svad]

Istg if there's questions on ANYTHING from the mechatronics yr 11 topic (somehow idfk ) I'm doomed

omg i loved the yr 11 mechatronics topic. It almost made me not wanna drop.

 

[Socialism]

I'm actually DONE FOR wtf


there's at least one person y'all are gonna beat

I'm still yet to do any revision (i.e i have literally no clue) on:

1. RPA vs BPA
2. Devops and mlops
3. idfk what the difference between ai and ml is
4. i can hardly remember the different kinds of learning like... supervised and unsupervised and then two others?
5. all of the regression algorithms
6. and i really should go over diagrams more

so basically it's over for me