archR: Identifying promoter sequence architectures de novo using NMF
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Updated
Jul 1, 2021 - R
archR: Identifying promoter sequence architectures de novo using NMF
A generalizable collaborative filtering approach for recommending new procedures to patients and their caregivers.
Multi-subject Single Cell Deconvolution
A movie recommender pipeline hosted on a local flask server using non-negative matrix factorisation (NMF)
A comparative analysis between 4 topic modeling methods: LDA, NMF, BTM and CoreEx
Quora questions that have no labelled category, and attempting to find 20 categories to assign these questions to.
Covered multiple topics in NLP via mini projects
My assignments for homework of Computational Data Mining course at Amirkabir University of Technology
My solutions for the assignments of my university course Pattern Recognition and Machine Learning
Project to recommend movies using non-negative matrix factorization
qWiki search helps user to gain knowledge about a topic in a jiffy. User enters topic and number of sentences he wants, as a result the user receives the relevant and latest sentences about the topic.
Deconvolution of CRC in organoid and fibroblast bulk data identifying epithelial cell types proportions
identify segments of customers by geography using unsupervised learning
PyTorch implementations of the beta divergence loss.
Simple NMF Algorithm in Python
Topic modelling
SCDC project, originally on: https://github.com/meichendong/SCDC. Support sparse matrix among other additions.
POC on Recommender Systems, one of the most trending and intriguing domain in machine learning. Mainly focused on Collaborative Filtering approach and Non-Negative Matrix Factorization models.
Decomposition of heterogeneous DNA methylomes
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