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Questions tagged [machine-learning]

For questions related to machine learning (ML), which is a set of methods that can automatically detect patterns in data, and then use the uncovered patterns to predict future data, or to perform other kinds of decision making under uncertainty (such as planning how to collect more data). ML is usually divided into supervised, unsupervised and reinforcement learning. Deep learning is a subfield of ML that uses deep artificial neural networks.

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How to calculate the entropy in the ID3 decision tree algorithm?

Here is the definition of the entropy $$H(S)=-\sum_{x \in X} p(x) \log _{2} p(x)$$ Wikipedia's description of entropy breaks down the formula, but I still don't know how to determine the values of $X$,...
Z. Reticulan's user avatar
0 votes
1 answer
108 views

Giraffe Chess - High Level Assessment

My high-level takeaway from Matthew Lai's Giraffe Chess Paper is that one would want to use broad, shallow game trees, with some method of evaluating the probability of a favorable outcome for a given ...
DukeZhou's user avatar
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40 votes
3 answers
33k views

Why is Lisp such a good language for AI?

I've heard before from computer scientists and from researchers in the area of AI that that Lisp is a good language for research and development in artificial intelligence. Does this still apply, ...
Alecto Irene Perez's user avatar
17 votes
1 answer
1k views

Are information processing rules from Gestalt psychology still used in computer vision today?

Decades ago there were and are books in machine vision, which by implementing various information processing rules from gestalt psychology, got impressive results with little code or special hardware ...
Gottfried William's user avatar
10 votes
2 answers
553 views

How can an AI system develop its domain knowledge? Is there more than just Machine Learning?

So machine learning allows a system to be self-automated in the sense that it can predict the future state based on what it has learned so far. My question is: Are machine learning techniques the only ...
Jake Marry's user avatar
6 votes
4 answers
2k views

What are some datasets to train an MLP on simple tasks? [closed]

I have implemented an MLP. Now, I want to train it to solve simple tasks. Are there any data sets to train the MLP on simple tasks, that is, tasks with a small number of inputs and outputs? I ...
David Price's user avatar
3 votes
2 answers
444 views

How can one intuitively understand generative v/s discriminative models, specifically with respect to when each is useful?

I'm trying to gain some intuition beyond definitions, in any possible dimension. I'd appreciate references to read.
Tejal's user avatar
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4 votes
4 answers
532 views

Must people tell an AI which algorithm it should use? Can an AI learn algorithms by itself?

I'm a freshman to machine learning. We all know that there are 2 kinds of problems in our life: problems that humans can solve and problems we can't solve. For problems humans can solve, we always try ...
user avatar
102 votes
4 answers
89k views

How can neural networks deal with varying input sizes?

As far as I can tell, neural networks have a fixed number of neurons in the input layer. If neural networks are used in a context like NLP, sentences or blocks of text of varying sizes are fed to a ...
Asciiom's user avatar
  • 1,171
1 vote
2 answers
4k views

Simple text recognition with neural network [closed]

In my attempt at trying to learn neural network and machine learning I'm am trying to create a simple neural network which can be trained to recognise one word from a given string (which contains only ...
Amit Hendin's user avatar
14 votes
2 answers
833 views

Should deep residual networks be viewed as an ensemble of networks?

The question is about the architecture of Deep Residual Networks (ResNets). The model that won the 1-st places at "Large Scale Visual Recognition Challenge 2015" (ILSVRC2015) in all five main tracks: ...
Erba Aitbayev's user avatar
16 votes
8 answers
29k views

How to classify data which is spiral in shape?

I have been messing around in tensorflow playground. One of the input data sets is a spiral. No matter what input parameters I choose, no matter how wide and deep the neural network I make, I cannot ...
Souradeep Nanda's user avatar
17 votes
3 answers
1k views

How would an AI learn language?

I was think about AIs and how they would work, when I realised that I couldn't think of a way that an AI could be taught language. A child tends to learn language through associations of language and ...
AvahW's user avatar
  • 275
24 votes
2 answers
1k views

Are there any ongoing projects which use the Stack Exchange for machine learning?

Are there any ongoing AI projects which use the Stack Exchange for machine learning?
Techidiot's user avatar
  • 349
18 votes
1 answer
507 views

Are these two versions of back-propagation equivalent?

Just for fun, I am trying to develop a neural network. Now, for backpropagation I saw two techniques. The first one is used here and in many other places too. What it does is: It computes the ...
Aspie96's user avatar
  • 181
5 votes
1 answer
736 views

How to replicate legacy systems with machine learning?

Let's suppose that we have a legacy system in which we don't have the source code and this system is on a mainframe written in Cobol. Is there any way using machine learning in which we can learn from ...
jcromanu's user avatar
  • 153
4 votes
1 answer
752 views

How to represent a large decision tree?

A system makes a decision basing on a large number of varied factors, following a "live" decision tree - one that is (independently, through other subsystem) updated with new decisions, new situations....
SF.'s user avatar
  • 464
23 votes
5 answers
4k views

What is the difference between machine learning and deep learning?

Can someone explain to me the difference between machine learning and deep learning? Is it possible to learn deep learning without knowing machine learning?
Addis's user avatar
  • 333
8 votes
1 answer
2k views

Selecting the right technique to predict disease from symptoms

I'm trying to come up with the right algorithm for a system in which the user enters a few symptoms and the system has to predict or determine the likelihood that a few selected symptoms are ...
quintumnia's user avatar
  • 1,183
9 votes
1 answer
550 views

What are the necessary components to make an AI agent capable of self-programming?

An AI agent is often thought of having "sensors", "a memory", "machine learning processors" and "reaction" components. However, a machine with these does not necessarily become a self-programming AI ...
Mithical's user avatar
  • 2,915
10 votes
4 answers
4k views

How does using ASIC for the acceleration of AI work?

We can read on Wikipedia page that Google built a custom ASIC chip for machine learning and tailored for TensorFlow which helps to accelerate AI. Since ASIC chips are specially customized for one ...
kenorb's user avatar
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0 votes
1 answer
124 views

What are the current approaches for AI to learn a foreign language just from English books?

I'm aware this could be a complex topic, however I'm interested in existing research projects or studies where people are attempting or have succeeded in teaching an AI a foreign language just by ...
kenorb's user avatar
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2 votes
1 answer
848 views

Are there any machine learning techniques to detect coding standard violations?

Are there any machine learning techniques (such as deep learning or evolutionary algorithms) to detect coding standard violations? Which one would be more suitable? I don't have any specific ...
kenorb's user avatar
  • 10.5k
7 votes
5 answers
2k views

How can action recognition be achieved?

For example, I would like to train my neural network to recognize the type of actions (e.g. in commercial movies or some real-life videos), so I can "ask" my network in which video or movie (and at ...
kenorb's user avatar
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5 votes
3 answers
154 views

Do specific units exists for measuring the intelligence of a machine?

We can measure the power of the machine with the number of operation per second or the frequency of the processor. But does units similar of IQ for humans exist for a AI? I'm asking for a unit which ...
latmos's user avatar
  • 51
6 votes
1 answer
172 views

Has any research been done on DNN Music?

DNNs are typically used to classify things (of course) but can we let them go wild with sounds and then tell them if we think it sounds good or not? I'd like to think after a training class has been ...
Andrew's user avatar
  • 63
10 votes
2 answers
789 views

What are the learning limitations of neural networks trained with backpropagation?

In 1969, Seymour Papert and Marvin Minsky showed that Perceptrons could not learn the XOR function. This was solved by the backpropagation network with at least one hidden layer. This type of network ...
S.L. Barth is on codidact.com's user avatar
5 votes
1 answer
745 views

How does an unsupervised learning model learn?

How does an unsupervised learning model learn, if it does not involve any target values?
kenorb's user avatar
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10 votes
2 answers
3k views

What's the difference between hyperbolic tangent and sigmoid neurons?

Two common activation functions used in deep learning are the hyperbolic tangent function and the sigmoid activation function. I understand that the hyperbolic tangent is just a rescaling and ...
bpachev's user avatar
  • 410
11 votes
3 answers
373 views

What is a deep neural network? [duplicate]

What is the definition of a deep neural network? Why are they so popular or important?
baranskistad's user avatar
17 votes
1 answer
534 views

Are search engines considered AI?

Are search engines considered AI because of the way they analyze what you search for and remember it? Or how they send you ads of what you've searched for recently? Is this considered AI or just ...
baranskistad's user avatar
31 votes
2 answers
1k views

How is a deep neural network different from other neural networks?

How is a neural network having the "deep" adjective actually distinguished from other similar networks?
kenorb's user avatar
  • 10.5k
12 votes
3 answers
601 views

What are the main problems hindering current AI development?

I have a background in Computer Engineering and have been working on developing better algorithms to mimic human thought. (One of my favorites is Analogical Modeling as applied to language processing ...
callyalater's user avatar
5 votes
3 answers
10k views

How can the generalization error be estimated?

How would you estimate the generalization error? What are the methods of achieving this?
kenorb's user avatar
  • 10.5k
104 votes
9 answers
17k views

What is the difference between artificial intelligence and machine learning?

These two terms seem to be related, especially in their application in computer science and software engineering. Is one a subset of another? Is one a tool used to build a system for the other? What ...
intcreator's user avatar
  • 1,335
14 votes
3 answers
1k views

How does noise affect generalization?

Does increasing the noise in data help to improve the learning ability of a network? Does it make any difference or does it depend on the problem being solved? How is it affect the generalization ...
kenorb's user avatar
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