Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web

A easy HMM program written with Python, including the full codes of training, prediction and decoding.

🔬 ♌ Bacterial ribosomal RNA predictor

This is a diacritization model for Arabic language. This model was built/trained using the Tashkeela: the Arabic diacritization corpus on Kaggle

VirBot: a protein-based RNA virus detector for metagenomic data

Discrete Hidden Markov Model (HMM) Implementation in C++

An official repository for tutorials of Probabilistic Modelling and Reasoning (2023/2024) - a University of Edinburgh master's course.

dEploid is designed for deconvoluting mixed genomes with unknown proportions. Traditional ‘phasing’ programs are limited to diploid organisms. Our method modifies Li and Stephen’s algorithm with Markov chain Monte Carlo (MCMC) approaches, and builds a generic framework that allows haloptype searches in a multiple infection setting.

Natural Language Processing Nanodegree from Udacity Platform, in which I implement Hidden Markov Model for POS Tagger, Bidirectional LSTM for English-French Machine Translation, and End-to-End LSTM-based Speech Recognition

Implementation of Viterbi algorithm and Hidden Markov Model in C++

Classifying English spoken digit by Hidden Markov Model

A Python library for working with and training Hidden Markov Models with Poisson emissions.

Simple English part-of-speech tagger : 93% accuracy

Set of Hidden Markov Models to recognize words communicated using the American Sign Language

Automatic Speech Recognition (ASR) system was implemented using the HMM toolkit for building HMM model using training data. Then, this trained HMM Model was used for recognising words and results revealed that 80.02% accuracy for Phoneme Level Acoustic Model and 79.36% accuracy for word Level Acoustic Model. This developed system can be used by …

Simple implementation of Hidden Markov Model for discrete outcomes/observations in Python. It contains implementation of 1. Forward algorithm 2. Viterbi Algorithm and 3. Forward/Backward i.e. Baum-Welch Algorithm.

Compact implementation of discrete Hidden Markov Models in C and Python.

An implementation of Baum-Welch.