A library for Crossmodal Supervised Learning Algorithm with Time Series Memory Recording & Long Short-Term Memory Networks
Project description
Cerebrum’s purpose is getting continuous data inputs from different types of perceptions as memory sequences that triggered according to predefined threshold values and creating a complex time based relations between those memories by Crossmodal logic and training multiple Long Short-Term Memory Networks with this extracted data. Lastly creating outputs triggered by a stimuli, using pre-trained Artificial Neural Networks.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
cerebrum-0.1.29.tar.gz
(15.5 kB
view hashes)
Built Distribution
Close
Hashes for cerebrum-0.1.29-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0512d6ccab4f76629def4f290441820a0962ca55b5f6434a6c3f0afecce631fc |
|
MD5 | 46a26c507fdcbb37bc79bc09047008c1 |
|
BLAKE2b-256 | f202c09f290783a2d1983923d30d28d9ae40b92424511818af3c26d4d931cce2 |