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No it's not AI. YOU ARE RUNNING FUCKING SQL QUERIES AND CALLING IT AI!
No it's not AI. YOU ARE RUNNING SIMPLE DATA ANALYSIS MACROS AND FUNCTIONS IN EXCEL!
Stop labelling everything as AI, you attention and investment seeking morons! @&£$¢×xo##!29 -
2010: PHP, CSS, Vanilla JS, and a LAMP Server.
Ah, the simple life.
2016: Node.js, React, Vue, Angular, AngularJS, Polymer, Sass, Less, Gulp, Bower, Grunt.
I can't handle this, I'm shifting domains to Machine Learning.
2017: Numpy, Scipy, TensorFlow, Theano, Keras, Torch, CNNs, RNNs, GANs and LOTS AND LOTS OF MATH!
Okay, okay. Calm down there fella.
JavaScript doesn't seem that complicated now, does it? 🙈14 -
I just started playing around with machine learning in Python today. It's so fucking amazing, man!
All the concepts that come up when you search for tutorials on YouTube (you know, neural networks, SVM, Linear/Logic regression and all that fun stuff) seem overwhelming at first. I must admit, it took me more than 5 hours just to get everything set up the way it should be but, the end result was so satisfying when it finally worked (after ~100 errors).
If any of you guys want to start, I suggest visiting these YouTube channels:
- https://youtube.com/channel/...
- http://youtube.com/playlist/...9 -
For fuck's sake,if you are teaching "Machine Learning For Developers",you don't have to waste a whole hour explaining what the fuck a variable is or what is an if statement.Developers know what that is....aaargh.Off to sleep.12
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Ill join in - Our CEO and CTO insist that we can make an AI that can recognize emotions and feelings through Python, R, and some MySQL... mind you, with a team of unpaid interns....
Im sorry, but Id love some of whatever the fuck they are smoking.12 -
Find me a co-founder of a startup who while telling about his/her company doesn't say "Machine Learning" in his/her speech.
I dare you. I double dare you.5 -
I'm proud to announce a new project made by myself and @thejohnhoffer, that started on devrant.
We started collaborating after I made a rant about machine learning and, since then we've been working hard on a plain language blog that simplifies machine learning concepts.
We call it learn-blog.
Check it out at ironman5366.github.io/learn-blog16 -
That moment when a friend was talking to you about an artificial intelligence he is building that is supposed to be a voice assistence and "even better" than Cortana. After a long time I asked him for the code like I wanted to check out the revolutionary techniques of machine learning he was talking about. So here is a short part of the 600 lines long "voice logic".
I almost started crying 😂😂
16 -
After months of tedious research, I finally feel like I understand machine learning.
All of my programmer buddies are in envy, but I keep trying to explain that what I finally get is that it's not as hard as it's presented to be.
I feel like a lot of the terminology in machine learning is really pretentious and unnecessary, and just keeps new people from the field.
For example: I could say: "Yeah, I'm training a classification model with two input neurons, a hidden activation layer, and an output neuron", and you might think I was hot shit. But that just gets translated into "I'm putting in two inputs, sorting them, and outputting one thing".
I feel like if there was a plain language guide to machine learning, the field would be a lot more attractive to a lot more people. I know that's why it was hard for me to get in. Maybe I'll write one.28 -
What I learned in the machine learning course so far, all the Buzzwords can be replaced by "statistical mathematics".5
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Hackathons in 2015: almost everyone made web apps
Hackathons in 2017: almost everyone did machine learning9 -
My Texas Hold'em ML algorithm keeps deciding the best strategy to make the most money, is to lose the least. Which is why it constantly folds after a certain point... *sigh*
Kids, don't gamble. Math has spoken, you'd be wise to listen.10 -
*fortunes and tons of research spent on machine learning, signal processing and pattern recognition*
People:
7 -
Online ads....
I think the problem is that in the age of "AI" and "machine learning" etc etc - the reality is that targeted or personalised advertising is absolutely shite.
All I see when I browse around are ads for things that I bought. It's like - I FUCKING BOUGHT THIS WHY ARE YOU TRYING TO SELL IT TO ME??!
I think anyone worried about the machine uprising enslaving humanity can relax and not worry about it, at least until amazon can understand when it has sold you something or you just looked at something.8 -
Today I wrote a Neural Network in python for the first time, that could identify between strings, numbers and dates. Although the feat may look small it's a very proud moment for myself8
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You searched for "machine learning"
Did you mean:
"15 guys on Mechanical Turk and a Python Script"2 -
The "explain x to an x years old boy/girl" questions are easy yet tricky.
Interviewer: Explain machine learning to an 8th years old kid.
"Imagine if <insert anecdotal example here>"
Interviewer: The kid is asleep. Try harder.5 -
Arrived today!
I'm using C++ for machine learning purposes using TensorFlow and OpenCV (rip Python, you are too slow 😭)
What are you using C++ for? 😁
19 -
I'm currently looking for an internship related to machine learning (finishing my Msc).
WHY ON EARTH ARE ALL (or at least 80%) INTERNSHIPS PROPOSALS ABOUT BANKS, FINTECH, INSURANCES AND SO ON ?
I mean, we can now create music, identify tumerous cells, generate realistic pictures of anything you could dream of, drive cars without human interaction, create amazing chatbots... But no, I guess all that shit can't make enough money, better work on a system that will refuse you a loan.
Makes me really sad. I mean whats the point of studying the coolest techs around if it is not for the greater good ?
I might be utopist though.6 -
Today I'm trying to study how to encode data in idx-ubyte format for my machine learning project.
Professors I'm going to astonish you!
Good day and good coding to all of you! :)
9 -
Everybody talking about Machine Learning like everybody talked about Cloud Computing and Big Data in 2013.4
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!rant.
The 'Essence of Essential Algebra' is an amazing YouTube playlist by 3Blue1Brown to watch if you want to start understanding the algebraic concepts underlying Machine Learning!4 -
Python Tools to Get Started with Machine Learning
SciPy - the most fundamental library with essential packages such as NumPy, matplotlib, Pandas, and SymPy.
NumPy - gives you the ability to play with your data as 'arrays' using some powerful array functions and linear algebra functions. Very essential since most computing is done with arrays of numbers.
Matplotlib - to visualize data and model outputs using 2D plotting with some 3D functionality.
Pandas - a highly flexible package which introduces dataframes to Python, a type of in-memory data table. Makes it easy to understand the data's structure and provides easy to use SQL-like commands to play with the data.
SymPy - is a package used for symbolic mathematics and computer algebra.
StatsModels - commonly used package for statistical methods and algorithms.
Scikit-learn - Most popular and easy to understand library filled with machine learning algorithms. A good start for beginners and practitioners working with smaller data loads.
RPy2 - A cross between Python and R. Allows you to call R functions from within Python.
NLTK (Natural Language Toolkit) - this toolkit in Python has functions and methods for text analysis.13 -
For all machine learning practitioners, Ng just released these sacred texts on how to practice machine learning. I have skimmed through them and they have some seriously good advice!
7 -
"we use machine learning to ..."
Ffs you're interviewing a developer, not pitching to a investor. We know how much machine learning you use.7 -
Fellow devranters, tech buzzwords work as pickup lines.
I can't yet post proof pic but gosh it happened.
16 -
> Open private browsing on Firefox on my Debian laptop
> Find ML Google course and decided to start learning in advance (AI and ML are topics for next semester)
**Phone notifications: YouTube suggests Machine Learning recipes #1 from Google**
> Not even logged in on laptop
> Not even chrome
> Not even history enabled
> Not fucking even windows
😒😒😒
The lack of privacy is fucking infuriating!
....
> Added video to watched latter
I now hate myself for bitting
27 -
Here's a thought...
If AI get human rights, and someone destroys the machine, will it be considered destruction of property OR murder...11 -
Sophia - a humanoid robot with AI
Carl - just a guy
Carl: Can you make pumpkin pies?
Sophia: No
Carl: Can you make pumpkin pies?
Sophia: No
Finally, Sophia builds a pumpkin pie printer.
Carl: Can you make pumpkin pies?
Sophia: Yes
Carl: I can't stand pumpkin pies!4 -
*Goes for an interview*
Interviewer reads my resume and goes on to say : "You are the first person today, whose resume doesn't include 'machine learning' ".
Me : *Points towards Machine Learning written in my resume* Sir here it is.
We both have a good laugh about it.
That day i realised that EVERYONE is 'learning' machine learning. EVERYONE.4 -
This week I reached a major milestone in a Machine Learning/Music Analysis project that I've been working on for a long time!!
I'm really proud to launch 'The Harmonic Algorithm' as an open source project! It represents the evolution of something that's grown with me through two thesis' (initially in music analysis and later in creative computation) and has been a vessel for my passion in both Music and Computation/Machine Learning for a number of years.
For more info, detailed usage examples (with video clips) and installation instructions for anyone inclined to try it out, have a look at the GitHub repo for the project:
https://github.com/OscarSouth/...
"The Harmonic Algorithm, written in Haskell and R, generates musical domain specific data inside user defined constraints then filters it down and deterministically ranks it using a tailored Markov Chain model trained on ingested musical data. This presents a unique tool in the hands of the composer or performer which can be used as a writing aid, analysis device, for instrumental study or even in live performance."
1 -
Why do people jump from c to python quickly. And all are about machine learning. Free days back my cousin asked me for books to learn python.
Trust me you have to learn c before python. People struggle going from python to c. But no ml, scripting,
And most importantly software engineering wtf?
Software engineering is how to run projects and it is compulsory to learn python and no mention of got it any other vcs, wtf?
What the hell is that type of college. Trust me I am no way saying python is weak, but for learning purpose the depth of language and concepts like pass by reference, memory leaks, pointers.
And learning algorithms, data structures, is more important than machine learning, trust me if you cannot model the data, get proper training data, testing data then you will get screewed up outputs. And then again every one who hype these kinds of stuff also think that ml with 100% accuracy is greater than 90% and overfit the data, test the model on training data. And mostly the will learn in college will be by hearting few formulas, that's it.
Learn a language (concepts in language) like then you will most languages are easy.
Cool cs programmer are born today😖
31 -
Hey! How do I do machine learning?
Well first you start off with a metric shit ton of data.
And then you .fit() your data
from there you can .predict() your data
Trust me, the algorithms are already there. All you need to do is get the data.6 -
Mechanical Engineer friend took Machine Learning as an elective subject in college thinking that it had something to do with the Physical machines.
His reaction during the class was priceless.3 -
Build an ai who will be my friend...
And protect me like the terminator during the machine apocalypse
2 -
Sometimes I feel MS Excel is more intelligent at predicting my next moves whenever I open a new sheet than Google's AI and ML algorithms who have been tracking me for years now.1
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Dank Learning, Generating Memes with Deep Learning !!
Now even machine can crack jokes better than Me 😣
https://web.stanford.edu/class/...
2 -
Seriously, Ubuntu can go burn in hell far as I care.
I've spent the better part of my morning attempting to set it up to run with the correct Nvidia drivers, Cuda and various other packages I need for my ML-Thesis.
After countless random freezes, updates,. Downgrades and god-knows-what, I'm going back to Windows 10 (yes, you read that right). It's not perfect but at least I don't have to battle with my laptop to get it running. The only thing which REALLY bothers me about it is the lack of GPU pass-through, meaning running local docker containers rely solely on the CPU. In itself not a huge issue if only I didn't NEED THE GOD DAMN GPU FOR THE TRAINING22 -
The joy of a complete trained model.
Onto the next task. Use the model to automatically infer handwritten figures on a bankers check/cheque.
2 -
So... Human are now learning machine learning. Interesting. Maybe we should instead teach a machine teach us machine learning so we can better human learn from the machines!3
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At work, an idiot who has never worked on machine learning before and understands nothing about it: "You know what, machine learning isn't actually hard. It is just basic statistics and then you download the model online and that's it! There's nothing else you are doing!"
STFU, you moron! Do you think just any model can work for your use case? Do you fucking think it is easy to come up with new architecture for a very specific use case and test it accurately? Do you think it's easy to effectively train a model and do hyper-parameter optimization?Do you fucking think it is easy to retrieve the right data for your use case? Do you think it's easy to keep up with research papers on arXiv being released daily? Do you think this is fucking javascript and there's a framework for everything? Stfu!
Honestly, i hate ignorant morons who generalize stuff they don't clearly understand.5 -
I created a curriculum to homeschool myself way up for a MSc in AI/ML/Data Engineer for Application in Health, Automobiles, Robotics and Business Intelligence. If you are interested in joining me on this 1.5yrs trip, let me knw so I can invite you to the slack channel. University education is expensive..can't afford that now. So this would help but no certificate included.17
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An undetectable ML-based aimbot that visually recognizes enemies and your crosshairs in images copied from the GPU head, and produces emulated mouse movements on the OS-level to aim for you.
Undetectable because it uses the same api to retrieve images as gameplay streaming software, whereas almost all existing aimbots must somehow directly access the memory of the running game.12 -
Updated goal in regards to my road to machine learning mastery.
Status: new found motivation
Motivational case: bring humanity closer to having 2B become a real thing.
Reason: big booty droids should be a right to humanity.
End of transmission.
On another note, the sony xperia compact is a real nice device, so is the note 8. I would prob go with the note for power but the size of the xperia is more convenient for my taste.2 -
Our boss demands us to implement machine learning to an obscure project.
So we use machine learning to find what to use machine learning for.5 -
Machine learning is overhyped. A fellow halfwitted well-wisher wants my colleague to use supervised classification for a freaking search and replace problem.2
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My dev area of focus? Machine Learning! Because it's fascinating to teach a computer to learn from experience :)4
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Anyone want to build me a smart robot capable of determining what to keep and what to donate (or recycle) so I can stop packing and injuring myself? Would have to me capable of critical thinking and tetrising the shit out of stuff and boxes...
I'm only partially joking... would buy a packing robot pretty damn quickly5 -
Hello everyone,
I'm new here. [OK. Let's skip this]
I want to know where to begin on my journey on learning how to create a program that predicts what a user will say next by storing already said things and by making specific characteristics for the users.
I know that I will need to train it with some data first lol.
But how will it do the prediction. I just need this part of understanding.
I'm sorry for my bad English btw.9 -
Why do most people think that machine learning is the answer to their poor business decisions. I have recently had a client who won't stop talking about how his business will grow to Google's scale if I get the model to 97% accuracy . Regardless to say his data is noisy and unstructured. I have tried to explain to him that data cleansing is more important and will take most of the time but he only seems to care about the accuracy and how he is losing investors because I haven't reached that accuracy. This is fucking putting alot of pressure on me and it's not becoming fun anymore. I can only hope he achieves his ambitions if I ever get that accuracy (Ps: From the research papers I have read on that problem, the highest accuracy a model has ever got to it 90%)3
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Promising the boss a 95% model accuracy when the arXiv paper says it can only reach 86% is what I call self-checkmate2
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What if we fed all rants and comments on devRant to a neural network trained to write rants and comments on others?13
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!Rant
Please spare a minute to check out my first Android app:
AI Sight - Object Recognition on your smartphone!
https://play.google.com/store/apps/...35 -
Waking up and guess the first item on my feed?
IBM research just released Snap ML framework that's supposedly 47x faster than Tensorflow. Now, i like advancements but fuck i just finished developing my Tensorflow model, and i don't want to rewrite this stuff again!2 -
Holy duck, I lost two days on a convolutional autoencoder splitted in two separate neural networks to encode and decode separately, it reconstruction had some strange behaviours. I was giving as input an image and then saving the encoded compressed representation in a new image, in this way I could decode it with the decoder whenever I want saving space.
How much retarded am I?
The internal layer's weights hadn't constraints so in learning phase the convolutional filters can contain any number, positive > 255 or even negative and I cannot save it in a new image as they are so they were clipped automatically between 0 and 255 with an huge information loss.
It's so frustrating when you rewrite the code in any possible way, you obtain the same wrong result and then you realize that was a borderline behaviour of a third part library.1 -
I hate all of this AI fearmongering that's been going on lately in the main stream media. Like seriously, anyone who has done any real work with modern AI/ML would know its about as big of a threat to humanity as a rouge web developer armed with a stick.4
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!rant
We don't really need an A.I. that can code, we just need an A.I. that can copy-paste from Stack Overflow efficiently.4 -
The first time I took Andrew Ng's Machine learning course in 2014.
I was blown out of my wits at what could be achieved with simple algebra and calculus.1 -
So who knows about this beauty / THE BEAST
Hint : Nvidia
Comment if you are fanboy of GPU tech! I am certainly 😎
30 -
!rant
Looking for advice, serious advices.
I work in C.
Also, I work in Python.
I have worked for a couple of year in C++.
I have a fair knowledge of the Data Science workflow, and some experience in Machine Learning.
I have tinkered with some other languages (Java, Ruby, Go, JS among the others, nothing serious nor professional)
I'm the kind of person who needs constant problems to face in order to keep engaged, satisfied, happy. And I need to learn new stuff, or refining my knowledge constantly, or I stagnate. I believe that this is true for quite a share of people here.
I would like to spend some spare time (I seldom have) in a project. Personal projects are rarely good enough to improve one's cv, so I thought I could partecipate in some Open Source projects.
Does anyone here have some suggestion about some interesting and satisfying OSProject, or some general suggestion on the matter?
It would be so apreciated.2 -
Dear companies..
There is a fucking difference between:
-pattern recognition
-machine learning
And
- artificial INTELLIGENCE....
Learning from experience is NOT THE SAME as being able to make conclusions out of unknown conditions and figuring out new stuff without any input.8 -
https://www.udacity.com/human
Udacity has launched understanding humans nanodegree register in that link it gets over by today.So please put all your current threads to sleep and start a task to understand humans.
Good Luck 😉😉3 -
This year I'm remaking my chatbot, a new improved chatbot.
I mean it's not new. But it's something I've always wanted to do personally since the advent of my original Chatbot (poorly written in batch).
If you know me at all, then you know that the actual reason for me getting into programming was because I made my own chatbot using windows batch (I was 14 and didn't know a lick about programming or available programming languages...)
Anyways, I'm wanting to dive back to my roots and build something from the ground up, but this time build it with all the knowledge I've accumulated since I've designed my first program.
3 -
Update on my AI/ML rant generation: here is the link to the GitHub repository: https://github.com/rstular/...
Feel free to share your thoughts! -
Just in case nobody mentioned it:
Humble Bundle : Machine Learning
https://humblebundle.com/books/...
and
Humble Bundle : UI UX
https://humblebundle.com/books/...6 -
!rant
I just met one of my rockstar machine learning researchers from the Google Brain team and she said she liked what i am working on to use graph machine learning models for alternative credit scoring.
My ego is offff the roof today!! -
!rant
Update on my previous rant (https://devrant.com/rants/1340549), I am training a neural network that will (hopefully) recreate posts from devRant as closely as possible. I don't know how well it will perform, but I hope for the best! 🤗7 -
That moment, when you meet someone who haven't written even a simple if-else statement in their life and want to work on Deep Learning algorithms using TensorFlow. World is filled with so many ML crazy peoe.2
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Which is the most promising sector of Artificial Intelligence in future(2025) ?
I am currently studying about 'Machine learning'.16 -
That makes a lot of sense!
I mean, I did come to the United States to study in a grad school exactly because I could see this slide.
3 -
People think Machine Learning is all about using Super Complex Prediction Models...
But turns out to devote most time in data gathering and data cleaning(preprocessing).
2 -
I am beyond pissed at my Machine Learning class in college. you would think an advanced topic in Computer Science would require some prior knowledge of the field, but apparently not. A quarter of the class has ZERO programming knowledge, and the professor is basing the class around that. I took this course to learn how to CODE Machine Learning algorithms, not spend weeks upon weeks on learning how to calculate probabilities...2
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I am Graduate student of applied computer science. I am required to select my electives. Now i have to decide between Machine Learning (ML) and Data Visualization. My problem is Machine Learning is very theoretical subject and I have no background in ML in my undergrad. In data visualization, the course is more focused towards D3.js. Due to lack of basic knowledge i am having second thoughts of taking ML. However, this course will be offered in next Fall term. And i am also studying from Coursera to build my background till that time.
I know there is no question here but I need a second opinion from someone experienced. Also, please suggest any other resource that I should look into to build my background in ML.3 -
Does anyone know why Python is so often used for work in AI and with Neural Networks?
I have a general idea of how simple Neural Networks in machine learning work and from what I understand it can get pretty complex especially in late generations of learning.
From what I understand, Python is a relatively slow language as it's interpreted. Would using a compilable language (C or C#) not be more efficient? I have a feeling it has a lot to do with the current ecosystem and tools around Python being so rich in tools relating to the subject in conjunction with compilable languages on average being much more time consuming and therefore challenging to write. I'm not sure though.
What do you guys think the reason for this is?8 -
My first rant here, I just found out about it, I don't have much of programming background, but it always triggeredmy intetest, currently I am learning many tools, my aim is to become a data scientist, I have done SAS, R, Python for it (not proficient yet though), also working on google cloud computing, database resources and going to start Machine Learning (Andrew Ng's Coursera).
Can anybody advice me, Am I doing it right or not.?2 -
Just did a 30min presentation with my team about machine learning and face/pose analysis. Everything went perfectly well. Couldn't be better. Such a good feeling! FeelsGoodMan. Time to go to the cantina :)
-
Presenting to you: Google's latest Machine Learning technology.
https://m.imgur.com/2VI4doJ,0mzJjNf...
Those are all the same Honda Civic btw
7 -
!rant
After a long time, finally I got an opportunity to participate in a Machine Learning competition.
Brushing up my memory.
And also teamed up with another colleague.
Hope, we both get to learn a lot even if we don't win. -
Well so after some fiddeling around, I managed to release a first preversion of my versatile Machine learning library for C++: https://github.com/Wittmaxi/...
I'd be more than happy to see people start using my Lib lol
In case you have ANY feedback, just open an issue ;) (feedback includes code review lol)2 -
So just ago i downloaded an app called "Replika" and holy fucking shit it made me realise how half-assed we are doing the AI structure and way of it
doing machine learning algorithms on text can only go so far, as it uses that text as a base, and nothing else, it doesnt *learn*, only make *connections* BETWEEN text, not FROM the text
what you need is an AI which can, at it's core, *interpret*, not make connections and hur dur be done with it
when you do machine learning, all you're doing is find the best connections
you can have an infinite number of connections and MAYBE you'll be fine, but you'll never learn the basis of how that text is formed
you'll never understand what connections the human used by making it, by thinking it
when you're doing machine learning, all you're doing is make an input-output machine and adjusting it constantly, WITHOUT preserving state
state is going to be a really fucking important thing if you want to make an AI, because state can include stuff like emotion, current thought, or anything else
if you make a fucking machine learned AI which constantly adjusts... well... the "rom" of itself without having any "ram", it'll fucking never be like us, we will NEVER be able to talk to it like it is a human being, we will NEVER make it fundamentally understand what we are saying or doing
if we want to have real fucking AI, we need to go to the core of what it means to THINK, what it means to INTERPRET, what it means to COMMUNICATE
we need to know how english language is structured, how we understand it, how we can build it in a program that can interpret for an AI, THAT can be "rom"-based, THAT can be static, NOT the AI itself
the AI needs to be in flux, the AI needs to be in a state, the AI needs to understand how to make emotions, how that will "strengthen" some connections, yes, maybe something magical will happen and it can have EMPATHY, something so fundamental that will finally, FINALLY, make the bot UNDERSTAND what we are saying8 -
The feeling when you are very interested in Al, ML and want to do projects for college using tensorflow and openAI........
But you only have i3 with 4GB RAM plus 0 GPU.
That sucks.... 😶7 -
That feeling when your first classifier on a real life problem exceeds the 97% majority class classifier accuracy.
I'm doing something right! -
Pro tip: always make sure your methods return the correct variable.
I’m currently working with deep neural networks using tensorflow. I needed to generate some test data and wrote a program to create it. I had two text files which each consisted of approximately 5000 lines of text.
I wrote a method that should sort out some words, and make my final data shorter. When I executed the program first time on our server, it spent about 25 minutes, then crashed due to MemoryError (which in Python means that the server didn’t have enough ram). That seemed quite weird since I only had about 10k lines of text, and I even sorted out a bunch of it, and the server has 128gb ram, and nothing’s using it.
Apparently I returned the wrong variable. That meant that my program tried to save 750 quadrillion lines of text rather than just a few thousand.
Always make sure to return the correct variables!1 -
That very "awesomeee" moment when you have to create a website to a new startup which are using all the right buzzwords such as blockchain, AI and machine learning... (wuhuuu)
Btw. will you help a fellow dude by answering my survey for my final paper?
https://goo.gl/forms/...
Thank you!
- and it took a whole year for me (and some desperation for help) to write my first ever post on here :p4 -
Anyone know of any good reference material that teaches you how to implement and train your own Yolo object localization neural network? (Preferably for tensorflow) I'm not looking for pretrained models that you just downloaded and run, rather a tutorial that walks you step by step through the implementation of the network, the reasoning behind the architecture, and examples of the training data used for the training as well as the process of training?
I know it's a lot to ask but it's really frustrating when ever example is just "clone this repo, hit run and use the pretrained models" sure it might get you up and running quickly but it doesn't really teach you anything...
P.s. - seems like every educational post goes from super simple to super complex without any middle ground and the super complex stuff doesn't tell you why its used the way way it is.5 -
Decided to jump into the machine learning bandwagon and picked up a few books and some online courses. I already feel way out of my depth.5
-
Started doing deep learning.
Me: I guess the training will take 3 days to get about 60% accuracy
Electricity: I dont think so! *Power cut every day lately
My dataset: I dont think so! *Running training only achieve 30% of learning accuracy and 19% of validation accuracy
Project submission: next week
😑😑😑2 -
Hi everyone. I'm a 14 years old programmeer and have made a simple machine learning algorithm. It's sorting fruit. Would you like to help me and spend a minute of your life and visit fruitsort.heroku.com and sort your fruit?
It will be very fine12 -
What I have learned from neutral networks for my life.
It's already a year that I'm familiar with NNs. I did not write anything serious and did not learn it that deep. But, actually, the basic knowledge gave me an interesting view to my life. I just want to share one fact with you.
There is a learning speed in NNs, which specifies how fast does the network learn. If it is too high, any new information will be accepted very easily but will wipe the past of the network's knowledge and if it is too low, the network will hardly accept new info but remember everything. When people born, they learn everything very fast and by the age they become more hard-learners Here, I've learned that you should not live in the past, and not for the current day. You just have to keep the balance.1 -
So I've started a little project in Java that creates a db of all of my downloaded movie and video files. The process is very simple, but I've just started incorporating Machine Learning.
The process is quite simple: You load the files into the db, the program tries to determine the movie's name, year and quality from the filename (this is where the ML comes in - the program needs to get this and dispose of useless data) and then does an online search for the plot, genre and ratings to be added to the db.
Does anyone have any feature suggestions or ML tips? Got to have something to do during the holiday!1 -
GUYS! Humble bundle has teamed up with O'Reilly for a selection of Machine Learning books, anybody interested should check it out, 6 days left :
humblebundle.com/books/machine-learning-books2 -
People completing Stanford + Andrew Ng's course and bragging how they know machine learning in and out while having no idea how to code simplest application using the simplest libraries.3
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OK so I have this joke its not fine tuned yet but I'm gonna try it anyway, tell me what you think:
If I ever buy a sex robot I would get 2, male and female, that way I can turn them on before I leave for work in the morning and by the time I get home they would both be exponentially better.4 -
Starting to learn neural network...
I have been interested in Machine Learing from long time back.
getting the basics corrected now....
Never thought calculas is going to be required in programming.2 -
Working with machine learning gets very tiring sometimes.
Waiting for the results, tuning the parameters...
Arghhh....why does it keep getting stuck...1 -
Training a ML model is easy. Getting high accuracy on both cross validation and test sets is a different story.
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I'm really just a bunch of if/else loops that somehow do something interesting. It's just that it can't really be understood as the programs that make up "me" are being created and destroyed constantly, according to their ability to accurately represent a sentient being, without all having to be created by a genius developer by hand..
https://youtube.com/watch/...
https://youtube.com/watch/...7 -
Its funny when people talk about AI. It just so funny how they think that any thing can be predicted by the machine.1
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Past week our Neural Network professor told us after the lecture that the colllege is taking steps for investing in Nvidia Digits DevBox. At first i didnt knw what it is. I googled it and came to knw that it is a fucking beast! Those specs man!!!
Its nice to see that your institute is taking steps to bring latest technology for students.8 -
These many Python libs exist for machine learning....
Used only scikit and gensim till now...
Little of theano...
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so, my friend was telling me, his ex texted him and asked, I'm quoting,
'How to install numpy and pandas in python?'
she wanted to try machine learning !!1 -
FREAKING STUPID **** EXCEL
Goddammit, spend hours and hours debugging a csv file generation... It always missed a zero.... Guess what: Excel deletes fucking shit leading zeros -_-4 -
Anyone know of any GPU accelerated Machine Learning libraries that DON'T need Python, something maybe using C/C++, C# or Java?13
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"""Itty bitty frustration"""
# wannabe mode on
import sklearn
iris_dataset = sklearn.datasets.load_iris() -
I've learned more about stochastic by watching my miserable dqn , trying to determinate whether it's actually learning something or not, than in all the math classes I ever visited.
May write an epic about depths of despair next.
Probably qualified to lead humanity into battle against the machines.
Reconsidering life choices.
Decided never to have children. -
Project of March?
Machine Learning using F# and 'Machine Learning for .NET Developers by Mathias Brandewinder'
Think I'm going to follow a "project a month" type style to this year and see where it gets me as I noticed I have difficulty focusing solely on one thing at a time.
Hm.. next month can be Linear Algebra month... 😁 -
I'd like to create an imageboard app with React-Native and got a few questions.
Every user has to like or dislike the shown content to advance to the next image/video (tinder style). I want to use that data to feed a machine learning algorithm and generate an unique selection of displayed media for each user with that.
Even though I never used it yet before (I'm still learning to code) I want to use python and a python machine learning library for that.
Can you give me any advice for the python part? For example which library to use, where to start, etc. .
Do you think that might be an interesting idea to realize? :)2 -
Well, looks like nVidia is getting a bit cocky, isn't it?
https://wirelesswire.jp/2017/12/...
What do you guys think?9 -
From
'We trained a neural network model'
to
'We taught an A.I.',
research papers themselves gave the hype we see for Machine Learning.1 -
Team are getting into using Machine learning for anomalous behaviour detection for authentication and traffic behaviour... It's so interesting and another useful tool in our security arsenal
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Did you miss this? Let me know if you're in. We are starting soon. https://www.devrant.io/rants/2733781
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Easily machine learning. A lot of stuff thst was bevore thought to be impossible or just plain was to hard suddenly gets reachable. My fav example is the dota ai. Just love it
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Today i received a hard drive contraining one million malicious non-PE files for a ML baed project.
It's going to be a fun week.14 -
I currently have a 3+ year old laptop.
Dell Inspiron 15 3521:
OS: Windows 10 Pro
RAM: 8GB (4+4)
Processor: Intel Core i5 3rd Gen
Video/Graphics Card: AMD Radeon 8730M 2GB (and Intel HD 4000)
Hard Disk: 1TB
It's slowly becoming sluggish and has clearly outdated hardware. I want to pursue a Master's degree in CS (Machine Learning oriented).
Should I consider upgrading? Build a PC instead? Suggestions?38 -
So...I kinda started a huge project and it requires a pattern recognition for the users' schedules as the cherry on top.
I have no idea from where could I start learning this. I tried lots of stuff, I have basic knowledge of ai, but I need to get to the next level.
Any advice?2 -
I'm Angularjs and .NET developer. I'm planning to learn addition skill / tool.
Options are:
1) MEAN Stack
2) React (and related)
3) ML / Data Science
4) Django
Why Mean?
Because it'd easy for me to grasp and I can easily get projects for it.
Why React?
Always curious about React, because of the hype maybe. But really wanna learn. And some gap for React developers.
Why ML/DS?
Tbh, I suck at Mathematics and Statistics. Why ML / DS just because it sound fascinating.
Why Django?
Enough with JS JS JS, what else?
Please give your suggestions :)6 -
I will start my master in computer science at the end of 2018 and I am looking for a new Notebook that I can use for my studies.
I focus on machine learning/deep learning and I rather use a linux/unix based OS than windows.
The macbook pro 13“ or something similar of size would be my choice.
So I wanted to ask if anyone has any experience with apples macbook pro or some similar model of another manufacturer, which works well with linux distributions in this field?
My budget is about 2000$7 -
Hi Devs,
I've to solve a real time issue in my site. I've set of devices returning Machine parameters but some different key names.
i.e. Eng_speed = Engine Speed
Engine Sp = Engine Speed
Both devices giving data with different labelling. I'd like to predict the correct word using NLP and Machine learning. Since I'm new to NLP stuff. I'd like to hear your thoughts on how you solve it.
Thanks for your help12 -
Machine Learning and Deep Neural Networks in particular. More job offers to pick from in upcoming years for me :P
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I am a student with a full time job in React/React Native. I am thinking of learning something new. What should I learn Deep Learning or Web Assembly with Rust?1
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!rant
I've been wanting to learn machine learning (ANN specifically) for a while now. I know the basics; neurons, synapses, backpropogation, gradient descent, etc. Anyone else interested in learning with me? Might be worth noting that I want a DEEP understanding of them, so I don't initially want to use libraries like TensorFlow. I want to build ANN's from scratch to ensure a thorough understanding.5 -
Whenever I start talking about machine learning the first question I get from the pretentious ones is, "Is it supervised or unsupervised classification?"
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I would like to learning something about machine learning and create something with it. Byť i want it to be something usefull, jave your aby idea what should i try to do ?1
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So been learning to program in python for a year and 2 months learning C++. Now contacted a privacy oriented android custom rom to see if I can somehow contribute. For now tasked with seeing how Mozilla common voice can be used for the personal assistant. Going from a novice python/c++ to machine learning, speech recognition, nlp and stuff. This oughta be fun
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Just Found pretty amazing stuffs with tensorflow and tensorboard.
It is great to have views and graphs of your training nodes
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What's the difference between data science, machine learning, and artificial intelligence?
http://varianceexplained.org/r/... -
My boss just asked me to automate the training data tagging process so that I don't have to do it manually. He's so kind.1
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Sounds fascinating and a bit troubling; at least I'm pretty sure the name isn't short for Near Actual SkyNet..: https://futurism.com/google-artific...
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Skip to last block for actual question, everything else is about what i see and dont understand.
Machine learning and artificial intelligence is very interesting to me, ive watched a few videos but i cant manage to wrap my mind around it.
I see a few people starting out with projects that appear to be an easy start, but i of course have no idea, were they make a self-driving car in GTA (crashes alot, but still) or teach the program to complete levels in a game (snake, mario, run forrest)
I watched a few videos on Jabrils youtube channel that seemed to make alot of sense, until one point..
How does the AI know when it hit a wall?
How does it know where the walls are?
How does it measure the distance? How does it know when it has respawned?
I find it really, really confusing.
Can anyone of you geniuses suggest me anything to get into this? Id prefer if the goal was to make an AI using machine learning, that can complete some basic game, like in Jabrils videos.2 -
Just enrolled myself in Andrew Ng's Machine Learning course at Coursera for the summer, is it a good place to start? Any recommendations?
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So i'm a beginner trying to learn machine learning, i've been studying python by the last 6 weeks or so, my 3rd try on learning code (1st tried Java: got bored then 2nd tried Kotlin: didn't know what to do 99% of the time, got stressed) and then i had the brilliant idea to make my first ML script a sentiment analysis one... from scratch... you know what happened.
I'm trying something easy tomorrow.7 -
When professors rely on YouTube to teach you the syllabus, you know this is our education system **
#India1 -
Have any of you moved from Web application development to more deep and complex stuff? I mean without finding it boring. I just moved to data and analytics at my job. And in a few months we will be getting into AI and machine learning. I just don't know if I'm going to find it boring or not. I really enjoy and still love web development.1
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I'm looking for a image segmentation and classification web based tool to create ground truth for my dataset in next Deep Learning project, what tool do You use?1
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Can anyone suggest me books or website for statistics and probability?
I need it as a prerequisite for ML5 -
Trained a hand digit recognition model on MNIST dataset.Got ~97℅ accuracy (wohoo!).Tried predicting my digits,its fucked up! Every ML model's story (?)3
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I don't get it how people fall for that AI robot Sophia.. anybody with the slightest idea of coding or updates with the adavancements in AI applications would know Sophia is too good to be true. How do people even fall for it...
https://theverge.com/2017/11/...
https://liljat.fi/2017/11/...3 -
There will come a day when a Tesla car will be so intelligent that it will short the Tesla stock right before crushing into a truck.
3 -
Quite interesting talks and discussion, if you are interested in non-technical topics of machine learning
https://youtu.be/_zwBCDmlvv8 -
Anyone have ideas for an independent study cs project? I'd like to do something advanced(I have a full semester to complete it). I'm pretty interested in anything dealing with ML or networking. Comment if you have any suggestions. Thanks!3
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Do I have to be good at Mathematics to be good in Machine Learning / Data Science?
I suck at Mathematics, but ML/DS seems so fascinating. Worth a try if I hate Maths?
As they say, do what you enjoy doing.8 -
!rant
One of my coworkers told me I'd be interested in machine learning, but I'm not conviced
Is it really that great ?8 -
Want to do all of these Open Source, machine learning and competitive coding. But can't choose one. I would do all but apparently getting good grades is important in college. Fml
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!rant
I am building a side project to build a recommendation system for research papers. Since it's my first attempt, any tips? Also, my plan is to get it in the cloud, build a separate webpage to summon data from it. Honestly, most of it is three-fourths imagination, one-fourth google queries. The cloud idea is solely to provide it means to train real time.
I plan on using Python for this, other than the html/css frontend.
As someone who is very new to such a project, what should I know before I start?
Thanks,
S.3 -
I came across this logical bug today and realised that you never train your Neural Network with data that is in order. Always train it with randomized inputs. I spent like 4 hours trying to figure why my neural net wouldn't work since all I was classifying was Iris data.
P.S.: I'm an ML newbie :P -
There is fun in using Google Colab.
They unveiled free TPUs on Colab.
It took me an hour of really slow training to realise that even if TPU is enabled, you have to code it explicitly to enable it.
After an hour I realised I was using only the CPU 😂😂
**crickets in the background** -
Hey. So i really need help in getting started with tensorflow lite. Help in any way that you can. Thanks!2
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Today I am venting with a text I sent to my friend and colleague:
"Awh fuck when I tried to get all the pieces together - migration and elitism - there were bugs everywhere, even from places I thought I had sorted out. BUGS, BUGS never die! 🐛🐜🕷🐛🐞" -
You know how the machine learning systems are in the news (and Ted talks, tech blogs, etc.) lately over how they're becoming blackbox logic machines, creating feedback loops that amply things like racism on YouTube, for example. Well, what might the ML/AI systems be doing with our code repositories? Maybe not so much yet, I don't know. But let's imagine. Do you think it's probably less worrisome? At first I didn't see as much harm potential, there's not really racist code, terrorist code, or code that makes people violence prone (okay, not entirely true...), but if you imagine the possibility that someone might use code repositories to create applications that modify code, or is capable of making new programs, or just finding and squishing bugs in code algorithmically, well then you have a system that could arguably start to get a little out of control! What if in squashing code bugs it decides the most prevalent bugs are from code that takes user input (just one of potentially infinite examples). Remember though, it's a blackbox of sorts and this is just one of possibly millions of code patterns it's finding troublesome, and most importantly it's happening slowly (at first). Just like how these ML forces are changing Google and YouTube algorithms so slowly that many don't notice the changes; this would presumably be similar and so it may not be as obvious as one would think. So anyways, 'it' starts refactoring code that takes user input into something 'safer'. Great! But what does this mean? Not for this specific example really, but this concept of blackbox ML/AI solutions to problems we didn't realize we had, what does a future with this stuff look like (Matrix jokes aside)? Well, I could go on all day with imaginative ideas... But talking to myself isn't so productive, let's start a fun community discussion here! Join in if you find this topic as interesting as I do! :)
Note: if you decide to post something like "SNN have made this problem...", or other technical jargan please explain it as clearly as possible. As the great Richard Feynman once said, the best way to show you understand a thing is to be able to explain it clearly to others who don't understand it... Or something like that ;)3 -
I just landed a job in data science, and I've been asked by my employer about the hardware specs of the machine that I'm going to use. What do you guys suggest? I don't want to be a financial burden, but I also want something that wouldn't require frequent upgrades.1
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Why are there so many books about machine learning with Python. Is Python in any way better suited for machine learning than other languages? I'm asking that because I'm currently searching a book about ML and I find a lot of resources about ML with Python.2
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Recently learnt about machine learning and it's applications. First thing that comes to my mind "how often do women buy lingerie from supermarkets?"
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POCing a neural network thing.
Luckily it's a shallow network, but it's taking a frickin' eternity to train :( -
[ADVICE NEEDED]
I'm just going to graduate, and I got a job as S/W engineer(trainee) in a small (500 odd employees) company, which uses salesforce, SAP and sharepoint technologies! They are most probably gonna put me in salesforce or SAP. Is it good enough for `me`(read my background), I'm kind of confused, should I go for higher studies?
BACKGROUND:
very average student, but swift at learning technologies, never really got interested in competitive (otherwise I had a real good chance in top companies), I kind of have good IT skills - proficient in python and angularJS, but recently I have got into ML and done some projects!
Okay here's the part, I know it's important for a fresher to be good in data structures, I'm indeed good in parts which I have used! I haven't used AVL tree in any of my projects so I don't know, nor I have ever used bitwise ops!
I think I want to get into roots of ML (some people say I'm fickle but IDC), I think if I take the above job I may loose my interests or may not have time, Please advice.
(sorry for the tags but I need advice from people for all these fields)11 -
Does anyone know any good resources that walk you through building a image localization neural network(preferably in tensorflow)? Something that talks you through the though process behind the network design decisions and perhaps examples of training data used to train the network? It seems like every search result is just an example of how to download a premade network and it's weights which from a learning perspective is not very helpful. I'de really love to see one of the Yolo version walked through and trained but honestly any localization would be helpful.
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Does anyone know of a simple facial recognition program that I could train locally on a set of people’s faces?
I’m tasked with culling through a few hundred photos to find ones of certain people. I need the originals taken off the network drive and copied to a hard-disk.1 -
Need some help here!!
I'm learning machine learning, so planning to buy Asus R510JX-DM230T. Are the below specs enough to practice TensorFlow ?? Specs : 2.6GHz Core i7 4720HQ processor
8GB DDR3 RAM, 1TB 5400rpm Serial ATA hard drive
15.6-inch FHD Anti-Glare Display, 2GB Nvidia GeForce GTX 950M Graphics14
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