智能检索张维为表情包

This is a web app that integrates GPT-3 with google searches

Implementation of word2vec in PyTorch

Place2Vec ground truth dataset

Machine translation is the task of converting one language to other. Unlike the traditional phrase-based translation system which consists of many small sub-components that are tuned separately, neural machine translation attempts to build and train a single, large neural network that reads a sentence and outputs a correct translation.

Machine learning pipeline to predict relevant categories based on a product name and product description, using NLP and Deep learning concepts.

Reference implementation of the paper "Word Embeddings for Entity-annotated Texts"

Convolution Neural Network for classification of semantic relations in a sentence

word embedding resources for sentiment classification

A simple python tool for embedding comparison

No description provided.

Hate speech detection from code-mixed Hindi-English tweets using deep learning models. This project reports an increment to the state-of-the-art in hate speech detection for English-Hindi code-mixed tweets. The models result in an improvement of about 12% in F-score over a past work that used statistical classifiers.

Learning Personality is a bachelor internship project that use neural networks to extract, from natural language (in particular reviews), personality traits, through automatic approaches. @unimib17/18.

A Forum-based Chatbot for Parents of Autistic Children, built using Word and Sentence Embeddings.

This repository features deep learning models implemented with TensorFlow and PyTorch, including FNN, CNN, RNN, LSTM, GAN, Transfer Learning, and Transformer & BERT, GPT Each model is built from scratch with explanations, optimized training, and comparisons between frameworks, offering hands-on experience in understanding core deep learning concept

Use Key NLP techniques to classify news articles into categories: Bag_of_Words (tf-Idf), word embeddings and BERT language model

Modern Local Code Editor with local ai assistant with multiple options. Currently Support C language. Using a C Programming Book for knowledge

Panama Papers analysis using Graph Analytics and Embeddings

Detailed analysis of the research project, carried out during my bachelor internship, entitled "Neural Networks for the Learning of personality traits from Natural Language". @unimib17/18.

Repository for the paper "RDFsim: Similarity-Based Browsing over DBpedia using Embeddings", containing the current version of RDFsim which is available through https://demos.isl.ics.forth.gr/RDFsim/ .

A collection of Natural Language Processing challenges and my solutions for them that include traditional methods and deep learning.

Predicting Supreme Court Decisions

Link prediction in a Citation Network using text and graph-based features. This work is part of the ALTEGRAD course in the MVA master.

A placeholder for my work in word embeddings and knowledge graph representations

No description provided.

Sense Embeddings for Word and Relational Similarity.

Our paper and project explore the notion of information overload with respect to the YouTube platform, and more specifically, deep learning methods and NLP techniques that solve information overload with respect to summarizing and compressing general viewership of a YouTube video comment section.

Transportation analysis with social social media data

thebest.gr Patras news crawling about pm2.5 - NLP Techniques - Word embeddings of body text - LSTM Forecasting prediction

POStURE - A Framework for Analyzing Political Speeches Evolution and Similarities with Learned Linguistic Representations