hey Sup Forums can we talk machine """"""learning""""""?
what are you guys working on?
i myself am doing a genetic fuzzy system that hopefully will be able to learn an objective and be able to eventually complete it (supervised, single-objective environment of course)
Hey Sup Forums can we talk machine """"""learning""""""?
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what's the input?
I kinda want to fuck around with image recognition, but all I did so far is building autistic websites for weebs. What would be a good start? Do I just download a working thing or is the standard way to write your own?
Goal would be archived if the program can determine the possible expressions of animu.
Pic related should be tagged happy, smug and maybe eating
good luck you NEET
joke's on you, I manage a sprint team of code monkeys and my superior is drowing in shit from the business, so since I'm paid to do some simple shit here and there I have enough time to code from work.
My Environment runs at home, but I also code here if I want to or if nano isn't enough.
At 2k€ after taxes it's fine for being employed here only 8 months.
i have multiple inputs at the moment
speed, direction, position and then a matrix of numbers that describe the surrounding environment
but i'd like to make him be able to adapt new inputs and outputs, maybe another time though
for image processing i'd say convolution neural net with a supervised learning approach
or you could do a neuro-fuzzy (or another kind of adaptive fuzzy approach) for the expression determination
not keen with the lingo but I'd assume i'd give the program a number of samples and then have it guess in the first phase, where i'll provide inputs to the accuracy to make it as "me" as possible.
So for the first stage it could just give me everything it finds with a percentage or something. Since I've only read about the principles so far I'll only start 2018 the earliest on that though.
alright
yeah the idea is to give him a set of training data and answers to them, in this case images of anime facial expressions, and then he will iterate through the list of images (with a large variety of expressions to avoid overfitting to a specific kind) and change the weights for each node depending on the accuracy of his prediction
with enough training the net should be able to differentiate between expressions
i think it would be quite effective if the neural net didnt make the decision, but rather returned fuzzified data of his prediction,, like, im 60% sure she's happy, 15% sure she's eating, and 25% sure she's smug, and then use a fuzzy controller to defuzzify and get the answer
im not that experienced with deep learning nets though, i could be wrong with the whole training stuff regarding convolutional neural nets when it comes to the bias of each neuron, but i'd assume those are still decided by trial and error (i.e. guess, get answer, update weights/biases, guess again on another image)
yeah that's also how I understood the principle when I learned about it for my boss who wanted to sell the knowledge but not learn it for himself.
I basically watched the Videos about LearnFun and PlayFun on Super Mario by some dude on Youtube and figured this is how neural networks should be done.
Computers can't "intelligence" for you, it's all comparing quantified data with some "status".
So I'd definitely go the fuzzy route and give my input to adjust the weightings.
i'm working on conv autoencoder, using Tensorflow
working on face recognition, using a network model based on the Facenet paper, paired with some SVM classification
currently aligning the youtube faces database, few 100K images
if you can gather enough labeled data, its shit
easy
but you will need alot of data
>4D brain
>Thinking in 4D
How does that even work? That would imply past, present and future are irrelevant. To you they seem like a stream of events flowing in one direction. You can observe all the events from start to end and intervene at any point in space/time.
What the fuck?
that being said, there are networks and models out there for facial expression detection, but trained with humans obvs, could be trained with animu tho
nice, how are you enjoying tensorflow?
rad, how does it differ in regards to efficiency and accuracy compared to for example using haar-cascades?
don't worry, it's normal your tiny brain cant understand this concept.
I failed maths in high school. Sucks to be a brainlet.
didnt really look into facial expression stuff,
but its probably faster as it just needs a network forward to generate a classification
face recognition, for example openface needs ~58.9 ms on CPU and ~13.72 ms on GPU for a single pass with torch
accuray depends on your training data
animu.date
don't underestimate the meme stash. After 1k guided training iterations I would unleash the thing on Sup Forums to fetch stuff for users to rate the accuracy, so training data should be no problem at all.
We here at animu.date SAP (shitposting assistance programs) are a megalomaniac bunch of me and user which will make Shitposting great again.
>Youkoso
>That would imply past, present and future are irrelevant.
> You can observe all the events from start to end
he thinks with our time as being singular and perceives events unchanging
hence the start and end of an event is irrelevant and contradictory because the entire event is already existent as a whole, observable from every given direction from his 4D perspective
What about higher dimensions? M-Theory goes all the way to 11 dimensions. How do I even perceive that?
not bad, the issue i encountered with haar-cascades and template comparison for face/iris detection was the amount of data that needed to be stored
i'd assume its less with a neural net
don't know, im a brainlet past 4 dimensions
Still scraping and images of boorus to train my cute girl neural net that I will use to sort them into folders.
Captcha guessing?
>nice, how are you enjoying tensorflow?
it's nice, bit pain but it still better than using caffe
try to understand the image and reproduce it
Smug? More like content.
>animu.date
Consider this :
>install browser plugin
>plugin reads Sup Forums post you're about to send
>apply sentiment analysis on said post
>recommends animu girl reaction pic based on result
pls r8 my idea
alright, ill probably try it out next time, caffe was shit
would you be able to produce an image without perceiving it?
bump
anyone still here?
Where do I start with machine learning? I know programming but no idea on machine learning or how it works
ML is a fad.
start simple
machine learning and ai is honestly a meme, but an neat one to keep yourself occupied with
do something that you could be able to do with a series of if-statements
like make a dot follow your cursor or a dot that avoids your cursor