Pinned Repositories
1styearhomework
awesome-community-detection
A curated list of community detection research papers with implementations.
belief_propagation_community_detection
Python implementation of the community detection algorithm based on belief propagation proposed in https://www.pnas.org/content/111/51/18144
bert
TensorFlow code and pre-trained models for BERT
biolink-model
Schema and generated objects for biolink data model and upper ontology
Capstone-Project
Build user communities from their posted content on Twitter using clustering and topic detection methods.
charm
Parsing and testing Juju charms
Chinese_sentiment_analysis
Tutorial for Chinese Sentiment analysis with hotel review data
CommunityDetection
Implements of community detection algorithms
CrowdSourcing
asifkhan2017's Repositories
asifkhan2017/ElecBERT
Improving Sentiment Analysis in Election-Based Conversations on Twitter with ElecBERT Language Model
asifkhan2017/NCBI_BERT
NCBI BERT, pre-trained on PubMed abstracts and clinical notes (MIMIC-III).
asifkhan2017/awesome-community-detection
A curated list of community detection research papers with implementations.
asifkhan2017/belief_propagation_community_detection
Python implementation of the community detection algorithm based on belief propagation proposed in https://www.pnas.org/content/111/51/18144
asifkhan2017/PyTorch-BigGraph
Software used for generating embeddings from large-scale graph-structured data.
asifkhan2017/DGP
Rethinking Knowledge Graph Propagation for Zero-Shot Learning, in CVPR 2019
asifkhan2017/biolink-model
Schema and generated objects for biolink data model and upper ontology
asifkhan2017/Capstone-Project
Build user communities from their posted content on Twitter using clustering and topic detection methods.
asifkhan2017/bert
TensorFlow code and pre-trained models for BERT
asifkhan2017/Zero-Shot-Action-Recognition-with-Two-Stream-GCN
I Know the Relationships: Zero-Shot Action Recognition via Two-Stream Graph Convolutional Networks and Knowledge Graphs
asifkhan2017/Identifying-Influential-Users
Tested and analyzed 9 algorithms for identifying influential spreaders in social networks
asifkhan2017/CommunityDetection
Implements of community detection algorithms
asifkhan2017/TriDNR
Tri-Party Deep Network Representation
asifkhan2017/Online-Social-Network-Analysis
Empirical Analysis of Predictive Algorithms for Collaborative Filtering, constructing a Social Network using Twitter Data, Community Detection and Link Prediction using Facebook ‘Like’ Data, Categorizing Movie Reviews based on Sentiment Analysis, Content-based Recommendation Algorithm using Python, Pandas, Numpy and scikit-learn.
asifkhan2017/networks
Social network anlaysis
asifkhan2017/Machine-learning-templates
Templates for regression ,classification,NLP etc.
asifkhan2017/generativeSSL
Deep generative model for labels for semi-supervised learning
asifkhan2017/jwescoder-CorpusOptima_OperationalCode
Contains fully operational working code for creating large, biomedically pertinent semantic spaces based on "clean corpora" scraped from public databases, in particular abstracts from the National Library of Medicine's Pubmed biomedical literature database. The resulting semantic space has multiple uses esp. training Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) models in text-mining modules and packages such as Gensim and scikit-learn. The CorpusOptima system allows for comprehensive, systematic, and efficient scraping of exclusively abstract text -- without XML header, author/location data, or other ancillary text -- from all abstracts in a given chronological stretch (month-by-month in the primary version), conveniently organized to store all the scraped text from a given month or year of Pubmed abstracts in a local file or database entry. For incorporation into Gensim, scikit-learn or other modules implementing LSA and other document comparison tools, the "corpora" (semantic spaces) are available in two forms, each corresponding to a saved simplejson text file in the primary version of the code: 1. a large list of comma-separated strings with each string -- representing a separate document -- corresponding to text from a single scraped abstract (akin to the "documents" variable in Radim Rehurek's first Gensim tutorial -- https://radimrehurek.com/gensim/tut1.html ) 2. a nested list with the external list containing numerous lists of single-word tokens, each internal list representing the stemmed, lowercased, depunctuated, stopworded tokenization of each abstract, and thus with each internal list again corresponding to a distinct document (akin to the "texts" variable in Radim Rehurek's first Gensim tutorial -- https://radimrehurek.com/gensim/tut1.html ). The basic code module first uploaded maxes out at 100,000 abstracts per scrape (the maximum allowed under the NLM eutils API); a looped variant allows for scraping > 100,000 abstracts up to the total catalogued for a given month or year. I have used this code to scrape NLM Pubmed abstracts on a month-by-month and year-by-year basis dating back to 1911, one of the first years when abstracts in general were systematically catalogued for biomedical publications, with the full semantic space (complete corpus) of biomedical abstracts -- housing tens of millions of documents in total -- being stored in public Dropbox and Google Drive directories (each file corresponding to one month's or one year’s worth of saved corpora) as well as a database under construction.
asifkhan2017/Chinese_sentiment_analysis
Tutorial for Chinese Sentiment analysis with hotel review data
asifkhan2017/1styearhomework
asifkhan2017/SocialNetworkAnalysis
Empirical Analysis of Predictive Algorithms for Collaborative Filtering, constructing a Social Network using Twitter Data, Community Detection and Link Prediction using Facebook ‘Like’ Data, Categorizing Movie Reviews based on Sentiment Analysis, Content-based Recommendation Algorithm using Python, Pandas, Numpy and scikit-learn.
asifkhan2017/scrapper
Facebook, Blog, Twitter, and Instagram Scrapper
asifkhan2017/CrowdSourcing
asifkhan2017/charm
Parsing and testing Juju charms
asifkhan2017/networkx-tutorial
Twitter Network Analysis with NetworkX