Difference between revisions of "Deep Learning"
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* [[Hierarchical Temporal Memory (HTM)]] | * [[Hierarchical Temporal Memory (HTM)]] | ||
* [[Deep Features]] | * [[Deep Features]] | ||
| + | * [[Activation Functions]] | ||
| + | * [[Backpropagation]] | ||
* [https://medium.com/@gokul_uf/the-anatomy-of-deep-learning-frameworks-46e2a7af5e47 The Anatomy of Deep Learning Frameworks | Gokula Krishnan Santhanam] | * [https://medium.com/@gokul_uf/the-anatomy-of-deep-learning-frameworks-46e2a7af5e47 The Anatomy of Deep Learning Frameworks | Gokula Krishnan Santhanam] | ||
* [https://pathmind.com/wiki/data-for-deep-learning Data for Deep Learning | Chris Nicholson - A.I. Wiki pathmind] | * [https://pathmind.com/wiki/data-for-deep-learning Data for Deep Learning | Chris Nicholson - A.I. Wiki pathmind] | ||
Revision as of 00:02, 11 July 2023
YouTube ... Quora ...Google search ...Google News ...Bing News
- Artificial Intelligence (AI) ... Machine Learning (ML) ... Deep Learning ... Neural Network ... Reinforcement ... Learning Techniques
- Other Challenges in Artificial Intelligence
- Deep Neural Network (DNN)
- Hierarchical Temporal Memory (HTM)
- Deep Features
- Activation Functions
- Backpropagation
- The Anatomy of Deep Learning Frameworks | Gokula Krishnan Santhanam
- Data for Deep Learning | Chris Nicholson - A.I. Wiki pathmind
- Neuroscience News - Deep Learning
Deep learning models are vaguely inspired by information processing and communication patterns in biological nervous systems yet have various differences from the structural and functional properties of biological brains, which make them incompatible with neuroscience evidences. “Deep Learning is an algorithm which has no theoretical limitations of what it can learn; the more data you give and the more computational time you provide, the better it is” Learning Multiple Layers of Representation | Geoffrey Hinton
