Embedding模型代码和学习笔记总结
🎤 Building a content-based podcast recommender system using NLP
Romanian Word Embeddings. Here you can find pre-trained corpora of word embeddings. Current methods: CBOW, Skip-Gram, Fast-Text (from Gensim library). The .vec and .model files are available for download (all in one archive).
🐬 Reviewer recommendation system for Pull Requests in github using social network analysis and topic modeling.
Topic extractor with the idea of generating labels using genism.n_similarity
this repo contains files for my analysis on disney land visitor reviews using NLP
This project explores the realm of Natural Language Processing (NLP) using Word2Vec and FastText models. Dive into domain-specific embeddings, analyze clinical trials data related to Covid-19, and uncover the power of AI and ML in understanding textual data.🌟
Natural Language Processing for Google Play Applications. Where sentiment analysis was used on reviews to decide on new features to recommend developers.
Twitter Sentiment Analysis
Exploratory Data Analysis on various data set.
This repository contains the implementation of our paper "Auto-labelling of Bug Report using Natural Language Processing". Our paper introduces an NLP-based method using bug report attributes, leveraging a neural network for retrieval.
The goal of the presidential vocabulary program is to find the most similar words to a given word based on all the speeches made by U.S. presidents. It uses Selenium to scrape transcripts of speeches from the Miller Center website.
Implementing Text Summarization techniques on 'CNN DialyMail' dataset, using both 'Extractive' and 'Abstractive' strategies.
The repository contains Jupyter notebooks for various NLP tasks.
Scraping the employee reviews of the company and extracting the main topics or issues employees are talking about.
Improve access to healthcare services and reduce costs.
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