[Java] Hidden Markov Model Implementation

This is my last post this year. So, I have decided to finish the HMM implementation before the end of the year.

I tried to make the project clean as far as possible to enable those who want to use it understandable and easy to use. However, this isn’t the final version, there are many things that I want to add to the API and other enhancements. Any updates will be added to the README of the repository.

– Here you can see the repository of implementation.

– To see the features, check the README file

– To check the javadoc of the whole project click here

The test model is taken from my own created HMM model using creately.com app.

HMM1

Posts related:

I will add the other 2 parts after finishing them.

That’s all. See you next year! 🙂

[Kaggle] Poker Rule Induction

I wrote a note http://nbviewer.ipython.org/github/AhmedHani/Kaggle-Machine-Learning-Competitions/blob/master/Easy/PokerRuleInduction/PokerRuleInduction.ipynb about Poker Rule Induction problem, the note explains the problem description and the steps I used to solve it.

It is considered a good problem for those who want to start solving at Kaggle and know about some Machine Learning libraries in Python that are commonly used when solving at Kaggle.