Natural Language Processing (classification and machine translation) codes and analysis done for the year long practicum in Dublin City University (2019-20)
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Updated
Sep 9, 2020
Natural Language Processing (classification and machine translation) codes and analysis done for the year long practicum in Dublin City University (2019-20)
RAG powered AI chatbot for Indian Language (Hindi) using LangChain, Ollama, Qdrant, and MLFlow
This repository presents and compares HeterSUMGraph and variants doing extractive summarization, named entity recognition or both. HeterSUMGraph and variants use GATv2Conv (from torch_geometric).
Repository for NLP tasks with Word2vec, Glove, Fasttext embeddings, RNN, LSTM, BiLSTM, Attention using NLTK, Gensim, Keras, Huggingface
A benchmark for embeddings evaluation for Kyrgyz language
Ce fut mon prémier projet NLP où j'ai réalisé la détection de spam en utilisant les algorithmes d'embedding pour encorder mes textes. J'ai utilisé Random Forest et Milti-Layres Perceptrons pour la phase de classification. Ce qui a pemit l'obtension des précisions respective de 97% et 98%. J'ai aussi appris à documenter mes codes via sphinx
Modern Information Retrieval Project
The project focuses on developing medical word embeddings using Word2vec and FastText in Python to create a search engine and Streamlit UI. The use of embeddings helps overcome the challenges of extracting context from text data, making it easier to represent words as semantically meaningful dense vectors.
Music Genre Classification with Turkish Lyrics
Course project for machine learning(cmu 10701, phd)
Extreme multiclass classification of product types.
Persian Social Media Sentiment Analyzer
Classification of acronyms and their long forms using an RNN (LSTM), CNN, and FFNN model. The experiments focused on the RNN and used different vectorisation methods and hyperparameters. Models were built with Keras and the notebook code runs on Google Colab.
Question answering using word embedding models (Word2vec , fastText , Glove)
Skip-gram and FastText models to perform word embeddings for building a search engine for clinical trials dataset with a Streamlit user interface.
Sentiment analysis using deep learning models and FastText embedding on Apache Spark
Some mini projects and training code
Topic Modeling on BBC News using Facebook's FastText embeddings and LDA probabilistic model.
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