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pyhsmm VS htm.java

Compare pyhsmm VS htm.java and see what are their differences

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pyhsmm logo pyhsmm

pyhsmm is a Python library for approximate unsupervised inference in Bayesian Hidden Markov Models (HMMs) and explicit-duration Hidden semi-Markov Models (HSMMs), focusing on the Bayesian Nonparametric extensions.

htm.java logo htm.java

htm.java is a Hierarchical Temporal Memory implementation in Java, it provide a Java version of NuPIC that has a 1-to-1 correspondence to all systems, functionality and tests provided by Numenta's open source implementation.
  • pyhsmm Landing page
    Landing page //
    2023-10-15
  • htm.java Landing page
    Landing page //
    2023-09-12

pyhsmm

Categories
  • Data Science And Machine Learning
  • Data Science Tools
  • Python Tools
  • Software Libraries
Website github.com
Edit details

htm.java

Categories
  • Data Science And Machine Learning
  • Data Science Tools
  • Python Tools
  • Software Libraries
Website github.com
Edit details

Category Popularity

0-100% (relative to pyhsmm and htm.java)

pyhsmm

htm.java

Data Science And Machine Learning
5 5%
Data Science And Machine Learning
95% 95
Data Science Tools
5 5%
Data Science Tools
95% 95
Python Tools
3 3%
Python Tools
97% 97
Software Libraries
50 50%
Software Libraries
50% 50

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What are some alternatives?

When comparing pyhsmm and htm.java, you can also consider the following products

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

NumPy - NumPy is the fundamental package for scientific computing with Python

OpenCV - OpenCV is the world's biggest computer vision library

Dataiku - Dataiku is the developer of DSS, the integrated development platform for data professionals to turn raw data into predictions.

Exploratory - Exploratory enables users to understand data by transforming, visualizing, and applying advanced statistics and machine learning algorithms.

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