A survey of machine learning papers.
record my reading papers and reproduction code.
A TensorFlow implement for "A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understanding".
人工智能学习资料超全整理，包含机器学习基础ML、深度学习基础DL、计算机视觉CV、自然语言处理NLP、推荐系统、语音识别、图神经网路、算法工程师面试题
Including Knowledge Graph and Neural Language Processing (especially information extraction) papers from 20 top conferences:
Machine Learning Resources
Nowadays almost all companies are working on Review Based Project Management techniques, So user reviews play a very crucial role in such a scenario so this model is able to rate each review on a scale of 1 to 5. BERT already have a pre-trained dataset of 6 different languages for this project, which made this model easier to develop. Then used …
ツイートを学習して文章生成する
Tweet Classifier with feelings(positive or negative)
Get Powerful quotes on your phone or pc!!! NLP WEB APP
NeuralNine is an educational brand focusing on programming, machine learning and computer science in general! Let's develop brains!
Utilizes Logistic Regression for automatic categorization of user comments into positive or negative sentiments. Ideal for gauging customer feedback, monitoring social media sentiment, and analyzing user comments. A robust solution for sentiment classification.
Unofficial implementation of asm2vec using pytorch ( with GPU acceleration )
Repositório destinado ao curso de Inteligência Artificial com Python (CS50AI).
Implements a sequence-to-sequence model with Long Short-Term Memory (LSTM) networks for accurate language translation. Utilizes deep learning techniques to seamlessly translate text from one language to another.
This project work as a NLP tool for precise identification and classification of named entities in text. Features state-of-the-art algorithms, customizable for various domains and entity types. Ensures fast and scalable processing of large text corpora.
2023 up-to-date list of DATASETS, CODEBASES and PAPERS on Multi-Task Learning (MTL), from Machine Learning perspective.
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