Difference between revisions of "Deep Learning"

From
Jump to: navigation, search
m (Text replacement - "* Conversational AI ... ChatGPT | OpenAI ... Bing | Microsoft ... Bard | Google ... Claude | Anthropic ... Perplexity ... You ... Ernie | Baidu" to "* Conversational AI ... [[C...)
 
(28 intermediate revisions by the same user not shown)
Line 1: Line 1:
[http://www.youtube.com/results?search_query=deep+learning+Neural+Network YouTube search...]
+
{{#seo:
 +
|title=PRIMO.ai
 +
|titlemode=append
 +
|keywords=ChatGPT, artificial, intelligence, machine, learning, GPT-4, GPT-5, NLP, NLG, NLC, NLU, models, data, singularity, moonshot, Sentience, AGI, Emergence, Moonshot, Explainable, TensorFlow, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Hugging Face, OpenAI, Tensorflow, OpenAI, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Meta, LLM, metaverse, assistants, agents, digital twin, IoT, Transhumanism, Immersive Reality, Generative AI, Conversational AI, Perplexity, Bing, You, Bard, Ernie, prompt Engineering LangChain, Video/Image, Vision, End-to-End Speech, Synthesize Speech, Speech Recognition, Stanford, MIT |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools 
  
* [[Other Challenges]] of Machine Learning
+
<!-- Google tag (gtag.js) -->
* [[Deep Neural Network (DNN)]]
+
<script async src="https://www.googletagmanager.com/gtag/js?id=G-4GCWLBVJ7T"></script>
* [[(Deep) Convolutional Neural Network (DCNN/CNN)]]
+
<script>
* [[(Deep) Residual Network (DRN) - ResNet]]
+
  window.dataLayer = window.dataLayer || [];
* [[Deep Belief Network (DBN)]]
+
  function gtag(){dataLayer.push(arguments);}
* [[ResNet-50]]
+
  gtag('js', new Date());
* [http://medium.com/@gokul_uf/the-anatomy-of-deep-learning-frameworks-46e2a7af5e47 The Anatomy of Deep Learning Frameworks | Gokula Krishnan Santhanam]
 
  
http://www.global-engage.com/wp-content/uploads/2018/01/Deep-Learning-blog.png
+
  gtag('config', 'G-4GCWLBVJ7T');
 +
</script>
 +
}}
 +
[https://www.youtube.com/results?search_query=ai+Deep+Learning+Technique+Model YouTube]
 +
[https://www.quora.com/search?q=ai%20Deep%20Learning%20Technique%20Model ... Quora]
 +
[https://www.google.com/search?q=ai+Deep+Learning+Technique+Model ...Google search]
 +
[https://news.google.com/search?q=ai+Deep+Learning+Technique+Model ...Google News]
 +
[https://www.bing.com/news/search?q=ai+Deep+Learning+Technique+Model&qft=interval%3d%228%22 ...Bing News]
  
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” [http://www.cs.toronto.edu/~hinton/csc321/readings/tics.pdf Learning Multiple Layers of Representation | Geoffrey Hinton]
+
* [[What is Artificial Intelligence (AI)? | Artificial Intelligence (AI)]] ... [[Generative AI]] ... [[Machine Learning (ML)]] ... [[Deep Learning]] ... [[Neural Network]] ... [[Reinforcement Learning (RL)|Reinforcement]] ... [[Learning Techniques]]
 +
* [[Conversational AI]] ... [[ChatGPT]] | [[OpenAI]] ... [[Bing/Copilot]] | [[Microsoft]] ... [[Gemini]] | [[Google]] ... [[Claude]] | [[Anthropic]] ... [[Perplexity]] ... [[You]] ... [[phind]] ... [[Ernie]] | [[Baidu]]
 +
* [[Other Challenges]] in Artificial Intelligence
 +
* [[Neural Network#Deep Neural Network (DNN)|Deep Neural Network (DNN)]]
 +
** [[(Deep) Convolutional Neural Network (DCNN/CNN)]]
 +
** [[(Deep) Residual Network (DRN) - ResNet]]
 +
** [[Deep Belief Network (DBN)]]
 +
** [[ResNet-50]]
 +
* [[Hierarchical Temporal Memory (HTM)]]
 +
* [[Deep Features]]
 +
* [[Backpropagation]] ... [[Feed Forward Neural Network (FF or FFNN)|FFNN]] ... [[Forward-Forward]] ... [[Activation Functions]] ...[[Softmax]] ... [[Loss]] ... [[Boosting]] ... [[Gradient Descent Optimization & Challenges|Gradient Descent]] ... [[Algorithm Administration#Hyperparameter|Hyperparameter]] ... [[Manifold Hypothesis]] ... [[Principal Component Analysis (PCA)|PCA]]
 +
* [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://neurosciencenews.com/neuroscience-topics/deep-learning/ Neuroscience News - Deep Learning]
  
 +
 +
<img src="https://adatis.co.uk/wp-content/uploads/ML-vs-DL.gif" width="800">
 +
 +
 +
Deep learning models are vaguely inspired by information processing and [[Agents#Communication | 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” [https://www.cs.toronto.edu/~hinton/csc321/readings/tics.pdf Learning Multiple Layers of Representation | Geoffrey Hinton]
 +
 +
<youtube>M8qdcOxDxgA</youtube>
 +
<youtube>53YvP6gdD7U</youtube>
 +
<youtube>N0ER1MC9cqM</youtube>
 
<youtube>b99UVkWzYTQ</youtube>
 
<youtube>b99UVkWzYTQ</youtube>
 
<youtube>P2HPcj8lRJE</youtube>
 
<youtube>P2HPcj8lRJE</youtube>
 
<youtube>CEv_0r5huTY</youtube>
 
<youtube>CEv_0r5huTY</youtube>
<youtube>7PiK4wtfvbA</youtube>
 
 
<youtube>Q9Z20HCPnww</youtube>
 
<youtube>Q9Z20HCPnww</youtube>
 
<youtube>Yr1mOzC93xs</youtube>
 
<youtube>Yr1mOzC93xs</youtube>
 +
<youtube>V8qrVleGY5U</youtube>
 +
<youtube>rJmBhnLzjOM</youtube>
 +
<youtube>WTnxE0wjZaM</youtube>

Latest revision as of 11:35, 16 March 2024

YouTube ... Quora ...Google search ...Google News ...Bing News



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