Machine Learning

Machine Learning messed up!

When your CPU is motivated and gives more than his 100%

What is machine learning?

Yes! 😎

Training till last breath...

Clever

That's exactly how I started, am I a Machine!? ... learning Machine Learning

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##!

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? 🙈

Shit getting to next level!

Interviewer: Can you start next Monday?
Me: it's 19

My life right now

Machine Learning

machine learning

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.

The only thing I am good at lol 😂

Credit : Programming Geeks Facebook group

Vision API fail

For the greater good ?

Le* Machine learning

Relatable?

what other computer scientist's think 😂

Found on Twitter (@svblxyz)

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.

Found this....

Machine Learning:

Presenting my research on fraud detection with Machine Learning

Look what I found!
Even my L3 cache is bigger than this!

“Those were the days😂”

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 😂😂

Always use Analogy when explaining things

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-blog

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.

Machine Learning Folks 😂

What I learned in the machine learning course so far, all the Buzzwords can be replaced by "statistical mathematics".

Polished statistics

Hype trends -

Money - Bitcoins

Tech - Machine Learning.

Agree ?

When beginners ask for Deep Learning tutorials.
Credits: Usaim Arif‎

Difference between machine learning and AI:

If it is written in Python, it's probably machine learning

If it is written in PowerPoint, it's probably AI

Machine Learning?

Person: I see you're training your neural net. How's it doing?
Me: Well...

Stolen from r/datascience

Hackathons in 2015: almost everyone made web apps
Hackathons in 2017: almost everyone did machine learning

Machine Learning is not easy 😂😂

*fortunes and tons of research spent on machine learning, signal processing and pattern recognition*

People:

🤔 🤔

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.

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 myself

Machine Learning be like...

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.

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.

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? 😁

!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!

You searched for "machine learning"

Did you mean:

"15 guys on Mechanical Turk and a Python Script"

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.

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! :)

Machine learning is super hard and frustrating. I have no idea where to start 😓

Everybody talking about Machine Learning like everybody talked about Cloud Computing and Big Data in 2013.

Me leaving my office on a Friday. 😂

"we use machine learning to ..."
Ffs you're interviewing a developer, not pitching to a investor. We know how much machine learning you use.

Machine Learning

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!

Typescript as a "Machine Learning" language wahhh???

And that's how we hacked a groupme chatbot

At first I thought fml means fuck my life but, it turns out, it means fuck machine learning.

Me : WTF ????

Some top-notch learning algorithms you have there Google 👌

> 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

No Cross Validation needed...

Here's a thought...

If AI get human rights, and someone destroys the machine, will it be considered destruction of property OR murder...

Interviewer: what's your biggest strength?
Me: I'm a fast learner.
Interviewer: what's 11*11?
Me: 65.
Interviewer: Not even close. Its 121.
Me: Its 121

Function to implement blockchain ML

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!

Titanic 😂😂😂😂

AI! BLOCKCHAIN! MACHINE LEARNING! BUZZWORDS!

AI are glorified ifs.
Now F off.

*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.

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😖

Change my mind.

99% Accuracy model from the first run!

Bypass me if u can :)

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.

Machine learning

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 TRAINING

I’m not scared of a machine that passes the turing test, I’m scared of the one that intentionally fail it

Code never lies
Comments sometimes do

Nah!
Code lies too, especially when you train a neural network 😂😂

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.

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.

The joy of a complete trained model.
Onto the next task. Use the model to automatically infer handwritten figures on a bankers check/cheque.

Build an ai who will be my friend...
And protect me like the terminator during the machine apocalypse

Google Assistant thinks I can't be smart :(

Don't Prepare to become a dinosaur

This bad boy just arrived! Excited for the new things ahead!

Check comments for more pics.

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.

101, How to get approval for your projects...
source: LinkedIn

Answer to the century old question.

Anyone know how to convince a client that machine learning will not be a magical solution to all their problems???

2019 is gonna be super interesting.

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.

For noobs 😂😂😂😂

Switching to macOS was an entry to paradise.

I go to Windows only to play Call of Duty. It’s crap and always will be.

P.S no comments on Linux.

This is what who I am

My dev area of focus? Machine Learning! Because it's fascinating to teach a computer to learn from experience :)

Machine learning is overhyped. A fellow halfwitted well-wisher wants my colleague to use supervised classification for a freaking search and replace problem.

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.

That magical moment when machine learning finally clicks in your brain. :)

Applying to colleges in the States for an MS in CS with a specialization in Machine Learning 🙂

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 quickly

Story of a ML Engineer. 😂😂😂

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%)

What if we fed all rants and comments on devRant to a neural network trained to write rants and comments on others?

Collected

Machine Learning is the evolution of being 'Technically Correct'

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.

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.

Building a Deep Learning environment on Windows is such pain in the ass.

Trying to learn machine learning with zero python background is frustrating as FUCK!

Save 100

!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.

So who knows about this beauty / THE BEAST

Hint : Nvidia

Comment if you are fanboy of GPU tech! I am certainly 😎

What have you brought me today? Tell me.

!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.

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.

And the journey begins.

!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!!

Hinton is Gawd 🙏

Weekend goals!

Some testing samples were being falsely detected by classifier, instead of improving classifier we removed those samples. :-D

If((currentTime - lastMouseClickTime) > 100000){
doupdate();
}

This is my understanding of "Machine Learning" in general

There are two sets of data:

1. In first data set, all the properties are known
2. In the second set, some properties are not known.

The goal of the machine learning is to find the value of the unknown properties of the second data set.

We do this by finding (or training) a suitable machine learning model (mathematical, logical or any combination of), that in the first data set, computes the value of the properties, which are unknown in second data set, with minimum error since we already know the real value of those properties.

Now, use this model to predict the unknown properties from the second data set.

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.

Leaving my Machine Learning project on overnight, let’s hope it works :)

Which is the most promising sector of Artificial Intelligence in future(2025) ?

I am currently studying about 'Machine learning'.

Machine learning still has a ways to go....
It thinks a cow statue is a car

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).

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.?

Actually I deploy my models using Google Slides and Microsoft Word

Machine Learning in a nutshell...

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.

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...

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.

!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.

buzzwords find their way into arm prosthetics

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 saying

Any recommendations on where to begin with "Machine learning",
and how intimidated should I be?

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 :)

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.

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!

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.

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.

Short question: what makes python the divine language for ML and AI. I mean i picked up the syntax what can it do that c++ or java cant? I just dont get it.

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.

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.... 😶

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 fine

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
😑😑😑

I think we need a machine learning algorithm to understand a woman’s mind

After a solid month of development. My model has finally reached 94% accuracy. And it appears to still be good (without the need to retrain) as new data keeps coming in :3

Oh gawd... I was waiting for this to get this good :3

Taking a dive into machine learning...pray for me!

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-books

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.

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.

My Loss/Time graph looks like a fun slide. Weeee. Woah. Weeee. Woah...

I am beginner in MACHINE LEARNING. How do I start to learning ML from scratch??

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!

When professors rely on YouTube to teach you the syllabus, you know this is our education system **

#India

Why is everyone into big data? I like mostly all kind of technology (programming, Linux, security...) But I can't get myself to like big data /ML /AI. I get that it's usefulness is abundant, but how is it fascinating?

Working with machine learning gets very tiring sometimes.
Waiting for the results, tuning the parameters...
Arghhh....why does it keep getting stuck...

These many Python libs exist for machine learning....
Used only scikit and gensim till now...
Little of theano...

I was once working on a deep neural network project(few years back when deep learning was just gaining momentum) and my project guide(alloted by the college) told me that this technology is useless and will be obsolete in near future. I don't know why he said that. Till this day I think what was the reason behind him saying that.

Now watching so much research done in this field, he might be realizing how much wrong he was.