What's the big difference between machine learning , deep learning and neural networks

Answer 1

Technically speaking, "machine learning" is a concept of making computer systems which are able to progressively improve their performance (a degree of success while performing a given task), without being specifically programmed to do so, based only on the data you feed them with.

Deep learning is a sub-field of machine learning, which aims to find the best data representations, rather than improving a task-oriented algorithm. Hierarchically stacked (layered) nodes are performing input-output function processing of the data. Those layers can be many, thus the "deep" part of the name.

Neural networks are those very structures which perform deep learning. Can be relatively simple, fully-connected, convolutional, recurrent and more. Each of the architectures is best suited for specific tasks, but that is another topic :)

https://www.sololearn.com/learn/714/?ref=app

Answer 2

https://www.sololearn.com/Discuss/430698/?ref=app
https://www.sololearn.com/Discuss/1021703/?ref=app

Answer 3

A neural network is an architecture.
Neural networks are used in deep learning.
Deep learning is a kind of machine learning.

@kuba Good explanation 👍