1a:I[27769,["/_next/static/chunks/a170c61f7e50ecf4.js","/_next/static/chunks/b3e45f8258255f01.js"],"default"] 19:T426,{"@context":"https://schema.org","@type":"BlogPosting","@id":"https://tutorialspoint.xyz/post/python-deep-learning-introduction#article","headline":"Python Deep Learning - Introduction","description":"Deep structured learning or hierarchical learning or deep learning in short is part of the family of machine learning methods which are themselves a subset of the broader field of Artificial Intelligence.","image":["https://tutorialspoint.xyz/brand.jpg"],"author":{"@type":"Person","name":"Mosh Hamedani","image":"https://api.tutorialspoint.xyz/uploads/avatars/user_28_1772198256.png","url":"https://tutorialspoint.xyz/profile/"},"publisher":{"@type":"Organization","name":"TutorialsPoint","logo":{"@type":"ImageObject","url":"https://tutorialspoint.xyz/logo.png"}},"datePublished":"2026-01-18T15:06:56.000Z","dateModified":"2026-01-18T15:06:56.000Z","mainEntityOfPage":{"@type":"WebPage","@id":"https://tutorialspoint.xyz/post/python-deep-learning-introduction"},"articleSection":["Python Deep Learning Tutorial"],"inLanguage":"en","isAccessibleForFree":true}1b:T4c4,

deep structured learning or hierarchical learning or deep learning in short is part of the family of machine learning methods which are themselves a subset of the broader field of artificial intelligence.

deep learning is a class of machine learning algorithms that use several layers of nonlinear processing units for feature extraction and transformation. each successive layer uses the output from the previous layer as input.

deep neural networks, deep belief networks and recurrent neural networks have been applied to fields such as computer vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, and bioinformatics where they produced results comparable to and in some cases better than human experts have.

deep learning algorithms and networks −

are based on the unsupervised learning of multiple levels of features or representations of the data. higher-level features are derived from lower level features to form a hierarchical representation.
use some form of gradient descent for training.

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