Artificial Intelligence Stack Exchange
Artificial Intelligence Stack Exchange

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.

Machine learning revolves around developing self-learning computer algorithms that function by virtue of discovering patterns in data and making intelligent decisions based on such patterns.

Machine learning explores the construction and study of algorithms that can learn from and make predictions about data. Such algorithms operate by building a model from the input, in order to make data-driven predictions or decisions, rather than following strictly static program instructions.

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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 are their differences and why are they…
intcreator
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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 network. How is the varying input size reconciled…
Asciiom
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What is self-supervised learning in machine learning?

What is self-supervised learning in machine learning? How is it different from supervised learning?
nbro
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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 most of the famous AI frameworks have primary…
Douglas Ferreira
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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 process word by word. Not only that but there is no…
DRV
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Are neural networks prone to catastrophic forgetting?

Imagine you show a neural network a picture of a lion 100 times and label it with "dangerous", so it learns that lions are dangerous. Now imagine that previously you have shown it millions of images of lions and alternatively labeled it as…
zooby
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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 idea about how they find the time complexity of…
user9947
39
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3 answers

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 the proliferation of neural networks and deep…
Alecto Irene Perez
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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. More specifically, an embedding can refer to a…
nbro
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What are examples of promising AI/ML techniques that are computationally intractable?

To produce tangible results in the field of AI/ML, one must take theoretical results under the lens of computational complexity. Indeed, minimax effectively solves any two-person "board game" with win/loss conditions, but the algorithm quickly…
k.c. sayz 'k.c sayz'
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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
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31
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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. The authors experiment with a neural network meant…
Surya Sg
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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 usually said something like "company A has a large…
user31556
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4 answers

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-random number? Does something like this already…
AshTyson
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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 could we build such a neural network? The…
Josef Ondrej
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