alexander-rakhlin/CNN-for-Sentence-Classification-in-Keras
quality grade D, 42 out of 100Convolutional Neural Networks for Sentence Classification in Keras
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Tokenization, parsing, classical NLP pipelines, translation and information extraction.
Signals: nlp, natural-language-processing, tokenizer, named-entity-recognition, text-classification, machine-translation, sentiment-analysis, spacy
637 results
Convolutional Neural Networks for Sentence Classification in Keras
SEAL (learning from Subgraphs, Embeddings, and Attributes for Link prediction). "M. Zhang, Y. Chen, Link Prediction Based on Graph Neural Networks, NeurIPS 2018 spotlight".
The code and data of ijcai2018 paper <Topic-to-Essay Generation with Neural Networks>
Predicting stock prices using a TensorFlow LSTM (long short-term memory) neural network for times series forecasting
A bidirectional recurrent neural network model with attention mechanism for restoring missing punctuation in unsegmented text
Traffic Flow Prediction with Neural Networks(SAEs、LSTM、GRU).
A simple neural network for python autocompletion
A neural network model for Chinese named entity recognition
Code Samples from Neural Networks for NLP
Convolutional Neural Network for Text Classification in Tensorflow
bert-base-chinese example
Build LLM-powered Dart/Flutter applications.
🔍 Search Engine for a Procedural Simulation of the Web with GPT-3.
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
CLUENER2020 中文细粒度命名实体识别 Fine Grained Named Entity Recognition
百度NLP:分词,词性标注,命名实体识别,词重要性
Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning And private Server services
This Word Does Not Exist
A powerful Swift framework for evaluating natural language math expressions
A List of Data Science/Machine Learning Resources (Mostly Free)
A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...)
Resources for "Natural Language Processing" Coursera course.
Text mining using tidy tools :sparkles::page_facing_up::sparkles:
The guide to tackle with the Text Summarization
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