Deep learning - Wikipedia
Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning. The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.
[2106.10165] The Principles of Deep Learning Theory - arXiv.org
2021年6月18日 · This book develops an effective theory approach to understanding deep neural networks of practical relevance. Beginning from a first-principles component-level picture of networks, we explain how...
What Is Deep Learning? | IBM
2024年6月17日 · Deep learning is a subset of machine learning that uses multilayered neural networks, to simulate the complex decision-making power of the human brain. ... However, CNNs now provide a more scalable approach to image classification and object recognition tasks, and process high-dimensional data. And CNNs can exchange data between layers, to ...
Introduction to Deep Learning - GeeksforGeeks
2024年5月26日 · In the fast-evolving era of artificial intelligence, Deep Learning stands as a cornerstone technology, revolutionizing how machines understand, learn, and interact with complex data.
Deep Learning: A Comprehensive Overview on Techniques, Taxonomy ...
In our taxonomy, we take into account deep networks for supervised or discriminative learning, unsupervised or generative learning as well as hybrid learning and relevant others. We also summarize real-world application areas where deep learning techniques can be used.
Deep Learning: A Comprehensive Overview on Techniques, Taxonomy ...
In our taxonomy, we take into account deep networks for supervised or discriminative learning, unsupervised or generative learning as well as hybrid learning and relevant others. We also summarize real-world application areas where deep learning techniques can be used.
The why, what and how of deep learning: critical analysis and ...
2023年3月26日 · First, we examine the concept of deep learning in light of the three fundamental questions “why”, “what”, and “how” and make assessments concerning its status in contemporary literature. Second, we discuss the compatibility between the idea of deep learning and the concepts of educational inclusion and adapted instruction.
What is deep learning and how does it work? - TechTarget
Deep learning is a type of machine learning (ML) and artificial intelligence (AI) that trains computers to learn from extensive data sets in a way that simulates human cognitive processes. Deep learning models can be taught to perform classification tasks and recognize patterns in photos, text, audio and other types of data.
The Principles of Deep Learning Theory
With an approach that borrows from theoretical physics, Roberts and Yaida provide clear and pedagogical explanations of how realistic deep neural networks actually work. To make results from the theoretical forefront accessible, the authors eschew the subject’s traditional emphasis on intimidating formality without sacrificing accuracy.
The Principles of Deep Learning Theory - Cambridge University …
The Principles of Deep Learning Theory An Effective Theory Approach to Understanding Neural Networks