Difference between revisions of "Hierarchical Temporal Memory (HTM)"
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|description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | ||
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| − | [ | + | [https://www.youtube.com/results?search_query=Hierarchical+time+history+future+Temporal+Memory+HTM YouTube search...] |
| − | [ | + | [https://www.google.com/search?q=Hierarchical+time+history+Temporal+future+Memory+HTM+machine+learning+ML+artificial+intelligence ...Google search] |
* [[Neuromorphic Computing#Temporal Computing | Temporal Computing]] | * [[Neuromorphic Computing#Temporal Computing | Temporal Computing]] | ||
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* [[Capabilities]] | * [[Capabilities]] | ||
* [[Clustering]] | * [[Clustering]] | ||
| − | * [ | + | * [https://www.analyticsvidhya.com/blog/2018/05/alternative-deep-learning-hierarchical-temporal-memory-htm-unsupervised-learning/ An Alternative to Deep Learning? Guide to Hierarchical Temporal Memory (HTM) for Unsupervised Learning | Tavish Srivastava] |
| − | * [ | + | * [https://www.youtube.com/user/OfficialNumenta Numenta HTM School] |
| − | * [ | + | * [https://www.slideshare.net/ibobak/hierarchical-temporal-memory-for-realtime-anomaly-detection Hierarchical Temporal Memory for Real-time Anomaly Detection | Ihor Bobak] |
| − | * [ | + | * [https://numenta.com/ Numentra - Where Neuroscience Meets Machine Intelligence] |
| − | * [ | + | * [https://www.youtube.com/user/OfficialNumenta Hierarchical Temporal Memory (HTM) School | Matt Taylor - Numentra] |
| − | * [ | + | * [https://numenta.org/ Numenta.org] |
| − | * [ | + | * [https://numenta.com/resources/biological-and-machine-intelligence/ Biological and Machine Intelligence (BAMI)] |
* [[Anomaly Detection]] | * [[Anomaly Detection]] | ||
| − | HTM are learning algorithms that can store, learn, infer, and recall high-order sequences. Unlike most other machine learning methods, HTM continuously learns (in an unsupervised process) time-based patterns in unlabeled data. HTM is robust to noise, and has high capacity (it can learn multiple patterns simultaneously). [ | + | HTM are learning algorithms that can store, learn, infer, and recall high-order sequences. Unlike most other machine learning methods, HTM continuously learns (in an unsupervised process) time-based patterns in unlabeled data. HTM is robust to noise, and has high capacity (it can learn multiple patterns simultaneously). [https://en.wikipedia.org/wiki/Hierarchical_temporal_memory Wikipedia] |
| − | + | https://upload.wikimedia.org/wikipedia/commons/0/05/Neuron_comparison.png | |
<youtube>-h-cz7yY-G8</youtube> | <youtube>-h-cz7yY-G8</youtube> | ||
Revision as of 18:16, 28 March 2023
YouTube search... ...Google search
- Temporal Computing
- Hierarchical Clustering; Agglomerative (HAC) & Divisive (HDC)
- Hierarchical Cluster Analysis (HCA)
- Capabilities
- Clustering
- An Alternative to Deep Learning? Guide to Hierarchical Temporal Memory (HTM) for Unsupervised Learning | Tavish Srivastava
- Numenta HTM School
- Hierarchical Temporal Memory for Real-time Anomaly Detection | Ihor Bobak
- Numentra - Where Neuroscience Meets Machine Intelligence
- Hierarchical Temporal Memory (HTM) School | Matt Taylor - Numentra
- Numenta.org
- Biological and Machine Intelligence (BAMI)
- Anomaly Detection
HTM are learning algorithms that can store, learn, infer, and recall high-order sequences. Unlike most other machine learning methods, HTM continuously learns (in an unsupervised process) time-based patterns in unlabeled data. HTM is robust to noise, and has high capacity (it can learn multiple patterns simultaneously). Wikipedia
Study of the Brain and Development of Intelligent Machines | Jeff Hawkins
