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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87
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14answers
13k 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? ...
63
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3answers
42k 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 ...
56
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10answers
36k views

Why is Python such a popular language in the AI field?

First of all, I'm a beginner studying AI and this is not an opinion-oriented question or one to compare programming languages. I'm not implying that Python is the best language. But the fact is that ...
48
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4answers
12k views

Are neural networks prone to catastrophic forgetting?

Imagine you show a neural network a picture of a lion 100 times and label with "dangerous", so it learns that lions are dangerous. Now imagine that previously you have shown it millions of images of ...
48
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3answers
40k views

What is self-supervised learning in machine learning?

What is self-supervised learning in machine learning? How is it different from supervised learning?
43
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4answers
64k views

How to select number of hidden layers and number of memory cells in an LSTM?

I am trying to find some existing research on how to select the number of hidden layers and the size of these of an LSTM-based RNN. Is there an article where this problem is being investigated, i.e., ...
32
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3answers
21k 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, with ...
30
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9answers
5k views

Is artificial intelligence vulnerable to hacking?

The paper The Limitations of Deep Learning in Adversarial Settings explores how neural networks might be corrupted by an attacker who can manipulate the data set that the neural network trains with. ...
29
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7answers
7k views

Computationally expensive AI techniques (that are promising)

To produce tangible results in the field of ML/AI, one must take theoretical results under the lens of computational complexity. Indeed, minimax effectively solves any two-person "board game" with ...
28
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2answers
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?
27
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7answers
14k views

How can an AI train itself if no one is telling it if its answer is correct or wrong?

I am a programmer but not in the field of AI. A question constantly confuses me is that how can an AI be trained if we human beings are not telling it its calculation is correct? For example, news ...
24
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5answers
20k views

What is the time complexity for training a neural network using back-propagation?

Suppose that a NN contains $n$ hidden layers, $m$ training examples, $x$ features, and $n_i$ nodes in each layer. What is the time complexity to train this NN using back-propagation? I have a basic ...
24
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2answers
952 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?
21
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7answers
2k views

If digital values are mere estimates, why not return to analog for AI?

The impetus behind the twentieth century transition from analog to digital circuitry was driven by the desire for greater accuracy and lower noise. Now we are developing software where results are ...
20
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5answers
22k views

Can a neural network be used to predict the next pseudo random number?

Is it possible to feed a neural network the output from a random number generator and expect it learn the hashing (or generator) function, so that it can predict what will be the next generated pseudo-...
19
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5answers
39k views

Why does C++ seem less widely used than Python in AI?

I just want to know why do machine learning engineers and AI programmers use languages like Python to perform AI tasks and not C++, even though C++ is technically a more powerful language than Python.
18
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4answers
4k views

How could we build a neural network that is invariant to permutations of the inputs?

Given a neural network $f$ that takes as input $n$ data points: $x_1, \dots, x_n$. We say $f$ is permutation invariant if $$f(x_1 ... x_n) = f(\sigma(x_1 ... x_n))$$ for any permutation $\sigma$. How ...
18
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1answer
433 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 ...
17
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6answers
2k 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?
16
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1answer
370 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 ...
16
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3answers
8k views

Why does the transformer do better than RNN and LSTM in long-range context dependencies?

I am reading the article How Transformers Work where the author writes Another problem with RNNs, and LSTMs, is that it’s hard to parallelize the work for processing sentences, since you have to ...
16
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2answers
4k views

Why has cross entropy become the classification standard loss function and not Kullbeck Leibler divergence?

Cross entropy is identical to the KL divergence plus entropy of target distribution. KL equals to zero when the two distributions are the same, which seems more intuitive to me than the entropy of the ...
16
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2answers
3k views

What is the “Hello World” problem of Reinforcement Learning?

As we all know, "Hello World" is usually the first program that any programmer learns/implements in any language/framework. As Aurélien Géron mentioned in his book that MNIST is often called ...
15
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2answers
1k views

When is deep learning overkill?

For example, for classifying emails as spam, is it worthwhile - from a time/accuracy perspective - to apply deep learning (if possible) instead of another machine learning algorithm? Will deep ...
15
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3answers
7k views

How to choose an activation function?

I choose the activation function for the output layer depending on the output that I need and the properties of the activation function that I know. For example, I choose the sigmoid function when I'm ...
15
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1answer
985 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 ...
14
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4answers
2k views

What activation function does the human brain use?

Does the human brain use a specific activation function? I've tried doing some research, and as it's a treshold for whether the signal is sent through a neuron or not, it sounds a lot like ReLU. ...
14
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4answers
4k views

What is the difference between latent and embedding spaces?

In general, the word "latent" means "hidden" and "to embed" means "to incorporate". In machine learning, the expressions "hidden (or latent) space" and "embedding space" occur in several contexts. ...
14
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2answers
672 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: ...
13
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3answers
531 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 ...
13
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1answer
3k views

Why do you not see dropout layers on reinforcement learning examples?

I've been looking at reinforcement learning, and specifically playing around with creating my own environments to use with the OpenAI Gym AI. I am using agents from the stable_baselines project to ...
12
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2answers
904 views

What is the difference between active learning and online learning?

The definitions for these two appear to be very similar, and frankly, I've been only using the term "active learning" the past couple of years. What is the actual difference between the two? ...
12
votes
1answer
18k views

Design AI for log file analysis

I'm developing an AI tool to find known equipments' errors and find new patterns of failure. This log file is time based and has known messages (information and error).I'm using a JavaScript library ...
12
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4answers
338 views

What are some tactics for recognizing artificially made media?

With the growing ability to cheaply create fake pictures, fake soundbites, and fake video there becomes an increasing problem with recognizing what is real and what isn't. Even now we see a number of ...
11
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3answers
668 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 ...
11
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2answers
11k views

What are bottleneck features?

In the blog post Building powerful image classification models using very little data, bottleneck features are mentioned. What are the bottleneck features? Do they change with the architecture that is ...
11
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4answers
2k views

What are the purposes of autoencoders?

Autoencoders are neural networks that learn a compressed representation of the input in order to later reconstruct it, so they can be used for dimensionality reduction. They are composed of an encoder ...
11
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1answer
430 views

How to stay a up-to-date researcher in ML/RL community?

As a student who wants to work on machine learning, I would like to know how it is possible to start my studies and how to follow it to stay up-to-date. For example, I am willing to work on RL and MAB ...
11
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1answer
907 views

What are all the different kinds of neural networks used for? [closed]

I found the following neural network cheat sheet (Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data). What are all these different kinds of neural networks used ...
11
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3answers
434 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 ...
11
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1answer
3k views

Loss jumps abruptly when I decay the learning rate with Adam optimizer in PyTorch

I'm training an auto-encoder network with Adam optimizer (with amsgrad=True) and ...
11
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4answers
12k views

Teach a Neural Network to play a card game

I am currently writing an engine to play a card game, as there is no engine yet for this particular game. I am hoping to be able to introduce a neural net to the game afterwards, and have it learn to ...
11
votes
4answers
228 views

How do I select the relevant features of the data?

Recently I was working on a problem to do some cost analysis of my expenditure for some particular resource. I usually make some manual decisions from the analysis and plan accordingly. I have a big ...
11
votes
4answers
1k views

What are the latest methods to train a chat bot?

I would like to train a bot that uses text input, memorizes a few categories and answers questions accordingly. In addition as version 2.0, I want to make the bot to answer voice inputs as well. Which ...
10
votes
4answers
323 views

What are the domains where SVMs are still state-of-the-art?

It seems that deep neural networks and other neural network based models are dominating many current areas like computer vision, object classification, reinforcement learning, etc. Are there domains ...
10
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3answers
236 views

What is a deep neural network? [duplicate]

What is the definition of a deep neural network? Why are they so popular or important?
10
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3answers
703 views

Does Monte Carlo tree search qualify as machine learning?

To the best of my understanding, the Monte Carlo tree search (MCTS) algorithm is an alternative to minimax for searching a tree of nodes. It works by choosing a move (generally, the one with the ...
10
votes
2answers
187 views

What does it mean for a neuron in a neural network to be activated?

I just stumbled upon the concept of neuron coverage, which is the ratio of activated neurons and total neurons in a neural network. But what does it mean for a neuron to be "activated"? I know what ...
10
votes
1answer
657 views

What are the implications of the “No Free Lunch” theorem for machine learning?

The No Free Lunch (NFL) theorem states (see the paper Coevolutionary Free Lunches by David H. Wolpert and William G. Macready) any two algorithms are equivalent when their performance is averaged ...
10
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3answers
15k views

Measuring Object size using Deep Neural Network

I have a large dataset of vehicles with the ground truth of their lengths (Over 100k samples). Is it possible to train a deep network to measure/estimate vehicle length ? I haven't seen any papers ...

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