All* Of Your Machine Learning Questions Answered

Author's preface: When perusing the archives I came upon this classic from 2017 that I now realize I never published on Vocal. Sadly, just as true today as it was then. Note that some of the language and imagery is not for the faint of heart. Enjoy!

1. What is Machine Learning?

Machine learning is a heavily used and widely abused technology term consisting of two words that when combined in that order, by their very definition, result in a logical contradiction. It is therefore nonsense. It isn’t anything, nor is it nothing, I’m not even talking about it right now, you just think I am, mind blown yet? Sometimes when two words are combined to form a new term they shed or morph their original meanings to become something entirely new. However, in this case advocates mean it exactly as it sounds, certainly the non tech savvy public believe that to be how it is meant. Machine learning is nothing more than using sophisticated algorithms developed with and employing advanced statistical and mathematical methods and models to process huge amounts of input data and outputting information in the form of more data, or predictions, or whatever as determined by their programming. In other words, computing as it has been done for the past 5–15 years depending on whom you ask. Somehow writing code and using it to program a computer to do things is “teaching” the computer, it is “learning”

2. How can I get rich off of this exciting new area on the cutting edge of technology knowledge?

Great question my young ward. It’s easy, remember part I of our series? No, well fuck off then. For those of you who were paying attention, in part I we discussed the magical world of hype. In the world of hype nothing is quite what it seems and everything is the greatest thing ever. Everyone makes money in the land of hype and nothing bad ever happens. It’s a lot like silicon valley in that…wait a minute I think I might be on to something here. Finally it is really easy to rest on your laurels once you have gained entry to hype world. Do not fall victim to that trap. Always try to kick up the hype another notch. For example, sure machine learning is a sexy hype term but what would happen if you added the simple word “deep” to the front end. Are you feeling the same stirring in your loins as I am? Now imagine getting “social network” into the mix, holy shit, I am fully erect just thinking about it. Time out I need to “take a bathroom break.”

3. I’m not that smart nor very well educated, can I still find employment in this ever growing field of the future?

Another great question and fortunately for you my young padawan the answer is a resounding yes. In fact one of the best online universities in the world the highly acclaimed UDacity, has the best machine learning course available anywhere for three thousand dollars. They don’t just accept anyone with a checkbook, or a credit card, or 3K in cash, you also have to be able to fill out the application and send it in. Even better, unlike all those shitty, accredited, nationally recognized, standard universities that hand out regular degrees like candy, when you “graduate” from “college” at UDacity you get a nanodegree. Yep, your eyes do not deceive you, a n a n o mother fuckin degree bitch. You know how many hiring managers cream their jeans when they come across a resume of a nanodegree holder? Well, do ya, do ya know how many actually cum or squirt right in their boxers or panties?. It’s a lot, a really big number. They are hearing it straight from the very highest levels of their respective organizations. The CEOs are practically screaming, “We need more nanodegree holders on staff and we need them now. Fuck those Ivy league assholes and state school jerk offs this is the digital future, universities are for libs, pussies, and gays, online is where its at and nano is the mano.” If you have the desire, the dedication, and access to three thousand dollars you could be that mano or womano. Just be alert for scammers, the online learning space is rife with them. One example is the almost identical Udemy. I like to remind myself they aren’t a real university like UDacity by reciting the following limerick. Some people U de me, some people U de I, but only anal penetrators go to fake ass U de my.

4. After I get my nanodegree in machine learning what kind of job can I expect to find?

I myself am a UDacity alum, or fightin Ude as we like to be called so I’ll take this one. When I first got my nanodegree in the mail I was so proud. My mom and dad were bragging to all their friends about their son, the first in the family to go to college and graduate. The very next day I hung it in my office at my job. It’s not really my office, it’s the bathroom but my manager at Arby’s was cool with it. He said it matched the general ambiance of the place. Mr. Spitz sure has quite the sense of humor. When I told him I was an expert in machine learning and had recently earned a nanodegree he said “That’s great kid. Can a machine learn to suck my dick? That nanodegree will go real nice with your nano-cock” Lol. Funny guy. Joke’s on him though because I recently started looking for a real job. I sent out my first batch of CVs (now that I am a nanodegree holder I have a CV not a resume like some nanodegreeless shithead). I only sent out 150 copies and got 2 phone interviews! They both went really well so I felt confident enough to put in my 3 months notice at Arby’s.

5. It all sounds too good to be true, is there any downside to the infinitely expanding, unbelievably awesome field of machine learning?

No, there is no downside. Now I gotta go, Mr. Spitz gets furious if I don’t scrub the urinals to a spit shine. Last week somebody took a dump in one, fuckin sick people out there. I wonder if a machine could learn to take a dump? I guess anything is possible in the future.

6. I just can’t give up the term machine learning, are there any options for using it in ways that aren’t nonsensical?

There actually are a few. One possibility is the inclusion of air quotes around the second word as in machine “learning.” An alternative to air quotes is the use of a question mark at the end as in machine learning? A third possibility is the addition of brackets around the entire term as in [machine learning]. This technique has the advantage of familiarity for philosophers and logicians who sometimes use it to indicate that certain nonsense terms should be set aside or ignored when making logical arguments/formulating logical analyses. The downside is how many fuckin logicians are there in the world these days? Am I right people?