pyHTM | Hierarchical Temporal Memory in Python

by carver Python Version: Current License: No License

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kandi X-RAY | pyHTM Summary

pyHTM is a Python library. pyHTM has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

This project is an unofficial implementation of the Cortical Learning Algorithms version of HTM, as described in v0.2 of the writeup. Ultimately, pyHTM will demonstrate learning and categorization of various sensory inputs, and display the results. This implementation will favor code readability over optimization when those options are mutually exclusive. If you want to understand what’s going on, just dig into src/htm_main.py and trace the code (using the Numenta paper as a reference). The project is very young, and still remains unproven in terms of correctness. I welcome bug reports, forks and pull requests.

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License

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Support

pyHTM has a low active ecosystem.

It has 91 star(s) with 32 fork(s). There are 15 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 2 have been closed. On average issues are closed in 18 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of pyHTM is current.

Quality

pyHTM has no bugs reported.

Security

pyHTM has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

pyHTM does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

pyHTM releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed pyHTM and discovered the below as its top functions. This is intended to give you an instant insight into pyHTM implemented functionality, and help decide if they suit your requirements.

Simulate the next column
Resets the stimulus
Simulate the given columns
Simplify the stimulation of the input cells
Gets the match data
Return the number of matches in the given dataSet
Returns a matrix of matching the match data
Returns True if all active synapses above the given threshold
Returns True if all synapses in the segment are above a given threshold
Returns True iff the motor is active
Capture all synapses for a given segment
Returns whether the connection is firing at a given time delta
Return a string representation of the synapse states
Returns True if the connection was fired
Return text representation of the cell
Convert a state to a string
Checks if all synapses in the segment are active
Generate the neighbors of the given column
Increase the permanences of all synapses

Get all kandi verified functions for this library.

pyHTM Key Features

No Key Features are available at this moment for pyHTM.

pyHTM Examples and Code Snippets

No Code Snippets are available at this moment for pyHTM.

Community Discussions

No Community Discussions are available at this moment for pyHTM.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install pyHTM

It’s preferred to run this inside a virtualenv:.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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