I suppose so - I guess it’s just a lot of directory traversal, formatting and moving annotations and images to the right spot. Idk aside from anything overly technical, it’s something an intern can do tbh

Data wrangling - getting everything formatted correctly before I hit ‘train’

r/learnmachinelearning

Get up to speed with probability, linear algebra and calculus 1 at the minimum.

Start with Python

Once you feel comfortable in both, start learning ML :)

High Paying, Highly Innovative, Highly Hyped = Recipe for oversaturstion of students studying it, oversaturation of middle career folks switching their careers into it, recipe for an oversaturated number of non-tech folks completing every LLM, DL certificates to post on their LinkedIn.

What happens with this oversaturation? Your raise the bar to entry - just like what leetcode culture did.

Yay toxic elitism 🤸‍♂️

Features are independent when conditioned on the dependent is pretty much what I know about Naive Bayes, I personally don’t care for the semantics.

Also the last time I was using naive bayes was grad school 7 years ago so things are fuzzy, sorry

(1/32)/(2/32)

Oh wait I made a typo, OP ignore my answer 😅

Uh not sure what Fubini’s theorem is, I just use the equivalence of P(X|Y)P(Y) = P(Y|X)P(X) = P(X,Y)

P(K=1) = 1/2

P(a=1|K=1) = P(a=1,K=1)/P(K=1) = (1/4)/(1/2)=1/2

P(b=1|K=1) = P(b=1,K=1)/P(K=1) = (1/8)/(1/2)=1/4

P(c=0|K=1) = P(c=0, K=1)/P(K=1) = (1/4)/(1/2)=1/2

P(a=1, b=1, c=0, K=1) = 0

P(a=1, b=1, c=0, K=0) = 1/8

[0.5 * 0.25 * 0.5] / (0 + 1/8) = (1/16) / (1/8) = 1/2

For conditionals, convert it into joints and priors first and THEN use the table to count instances out of N samples.

P(X|Y) = P(X,Y)/P(Y)

:)

Do you mean simply using the CUDA/cuDNN stack to build a project? Everything should be free

I don’t - I rather focus on drilling every nook and cranny of the attention mechanism so that reading any of these papers becomes easier.

I’d say if you truly understand Transformers both theoretically and intuitively, you’re already in the top 10% of MLEs. Though I’d imagine most PhDs understand it.

I’m on my 2nd ML role and theyre paying for my part-time PhD. Work life balance is brutal, making me a weak student, but coming out of it, I’ll have 9 YOE of pure MLE + a PhD in ML. So I should be set for life really haha 😗

🧍‍♂️🤸‍♂️ TIL there’s an MLE Professional Exam

I think that ‘flood’ is contributing to a market saturation of applicants, thereby making the process more selective.

We also can’t ignore the rapid influx of CS students increasingly choosing to study AI/ML versus say general SWE, web development, mobile app engineering like they did a decade ago.

I totally expect there to be a new standardized ML interview process in the same way Leetcode crept up with the tech boom

I still haven’t published yet and I’ve been here 4 years now. I’m part-time though so I can barely find time.