#compsciblr

saturday 12/09/2020

had my first day of lectures yesterday for my final year. i think it’s going to be a challenging one but i can’t wait to be busy again.

we have assignments already, web game programming sprints that i think will be fun!

"i did my phd on him. so i spent six years with this one guy, which, normally, would be a sign of a healthy relationship, but not in this case"

prof 1 "don't worry about the oral exam, it's great fun!”   prof 2 “yeah... for us”

"linguistics should bear in mind that non-linguistics, or, as i like to call them, normal people, don't understand this"

student "you mentioned in the previous slide a lot of extra readings"   prof "yes"   student "would you suggest that we read-"   prof "no"

"it could be an issue with your data. As we like to say in the machine learning world - garbage in, garbage out, wha'd'ya expect?"

"so if there are no other questions, then you have the homework, you know your test date, and i wish you a lot of... strength. For both of them"

"Today we're going to be talking about-"   *dramatic pause*   "-the SPACE PROBLEM!"   *everyone cheers*   "Now, now, settle down, before you get too excited, I don't mean the space, moon, buzz aldrin, astronaut, nasa, super cool and exciting space problem... I mean the computer space problem. Like indexing"

"the next example is a lot more substanial, so if you look at this and you think, whew, this is a lot of work, then... uh, yeah, you'd be right"

prof 1 "think of what we can do with technology now, especially in this area. Where are the ethics? We have these... how should I say... uh... gosh, i don't know how to phrase this... there's really no polite way of putting it... um... lets say... ‘companion’ robots?"   prof 2 "you mean sex bots"   prof 1 "well OBVIOUSLY i meant sex bots, david, but i didn't want to say that!"

"unfortunately it's necessary for you to go through this. you need to study and learn and do the assignments and do the exams and, yes, you must suffer... but enough with the damnation sermon, let's move onto the next chapter of hell"

"you need to find similarity in all the different tasks and then try to wisely use copy and paste. look at me, look. at. me. i said wisely"

student "i used 11 output features instead of 10"   prof "okay. and?"   student "i just want to know if that was wrong to do"   prof "did it work?"   student "yeah"   prof "then yeah. what do you want me to do? if it works, don't question it"

"if you don't save everything to your google drive then you might lose it, so for example, if you spend an entire day working on this machine learning assignment and you forget to save it, then you might just be ever so slightly disappointed"

"we decided to switch from r to pytorch because we decided that the lives of students were too easy so we wanted to make everything even more difficult" *awkward silence* "that was joke" *nervous laughter* "not really though"

"we'll be examining this horrible horrible subject through a very appropriately named program known fondly as brainfuck"

"i'm already looking forward to the christmas party where my uncle will ask me ‘so you make software for libraries huh? but libraries don't need software’ and i can say ‘well aunt sarah doesn't need you either, daniel, and yet you're still around’ and then i can explain what i do to him"

Part 1 | Part 2 | Part 3 | Part 4 | Part 5 | Part 6 | Part 7 | Part 8 

"if you can do this coding problem, the quality of your life will increase and your test score will too"

"So, i am sorry for the confusion... I was also confused"

"A lot of people are complaining now that models don't react the way that people do. My response to that would be, who cares?"

"this was fun right? the exam will be even MORE fun"

Prof who doesn’t speak English natively: "who needs a break?"   Student who does speak English natively: "i wouldn't say no"   Prof having a mild mental breakdown: "... that’s too difficult a sentence. i don’t understand that, i can't parse that, what the hell is that?!"

"it was an interesting task because people are very bad at it, but machines are very good at it"

"Most colleagues are very confused with neural language models because computers aren't capable of common sense or reasoning, so quite frankly this stuff just... shouldn't be possible"

"it was a beautiful time where linguistics and computer scientists could work together in peace and harmony... but not anymore"

Prof who doesn’t speak English natively: "the goal in chess is to get your opponent mated... is that how you say it in english? mated? you want to mate your opponent?"    Student who does speak English natively: "only if you're his wingman"

"so, size matters, it seems to be the only thing that matters... for machine learning specifically and NOT for anything else, alright ladies?"

"any questions? thoughts? feedback? fears? hopes and dreams? life advice? i may be in my forties but i could still do with some life advice"

"What i'm teaching you about NLP will probably be useless in five years time... but until then, you still have to study it anyway"

Prof: "so we're examining modern british literature, but what does that actually mean? what is modern? what is literature? and most importantly, how would you describe the term “british”?"    Student: "overrated"

"last year i didn't give the students this part of the code and there was almost a revolution. so this year, under the threat of being disposed, here is the code you need to contine"

"the advantage of this, is that we're talking to engineers again"

"the guy asked the chat bot "how would you feel if i turned you off?" and the chatbot replied "it would feel like dying" so the guy felt bad for it and left google... hard to believe he was an engineer"

Part 1 | Part 2 | Part 3 | Part 4 | Part 5 | Part 6 | Part 7 | Part 8

A little about me: I'm 23. I speak Hebrew and English fluently (feel free to practice with me!). I like to write and create which is why I'm in EngLit but IS is for my career lol because no one gets rich as a writer. I'm not great at the aesthetic, cutesy posts but my goal is productivity and reliability so that's what I'll be focusing on.

Degree: Digital Humanities : half English Lit and half Information Systems

Current Average: 75 (as of 12/5/23)

Goal: graduate with an average of 80 - therefore, get at least 80 in Stats, DiffEQ2, and my final semester classes, and 90s in my other three classes... Well. That's a tall fucking order, huh.

Classes Left:

This semester:

Stats

Algorithms

Summer Sem

Databases

Next Year Sem 1

DiffEQ2

Analytics

Next Year Sem 2

Undetermined Elective

Final project

SMART goal for this semester:

Study schedule:

3 hours of studying algorithms every Tuesday

1-2 hours of studying statistics every Thursday.

By using this blog to document my studying I will be held accountable for commiting to my study time-frames, hopefully with favorable results