Ml ProjectsML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xgboost in Python
Stars: ✭ 127 (-57.38%)
Chinese Text ClassificationChinese-Text-Classification,Tensorflow CNN(卷积神经网络)实现的中文文本分类。QQ群:522785813,微信群二维码:http://www.tensorflownews.com/
Stars: ✭ 284 (-4.7%)
Nlp chinese corpus大规模中文自然语言处理语料 Large Scale Chinese Corpus for NLP
Stars: ✭ 6,656 (+2133.56%)
Eda nlpData augmentation for NLP, presented at EMNLP 2019
Stars: ✭ 902 (+202.68%)
Deeplearning Nlp ModelsA small, interpretable codebase containing the re-implementation of a few "deep" NLP models in PyTorch. Colab notebooks to run with GPUs. Models: word2vec, CNNs, transformer, gpt.
Stars: ✭ 64 (-78.52%)
ShallowlearnAn experiment about re-implementing supervised learning models based on shallow neural network approaches (e.g. fastText) with some additional exclusive features and nice API. Written in Python and fully compatible with Scikit-learn.
Stars: ✭ 196 (-34.23%)
Vaaku2VecLanguage Modeling and Text Classification in Malayalam Language using ULMFiT
Stars: ✭ 68 (-77.18%)
Nlp In PracticeStarter code to solve real world text data problems. Includes: Gensim Word2Vec, phrase embeddings, Text Classification with Logistic Regression, word count with pyspark, simple text preprocessing, pre-trained embeddings and more.
Stars: ✭ 790 (+165.1%)
Text ClassificationImplementation of papers for text classification task on DBpedia
Stars: ✭ 682 (+128.86%)
Few Shot Text ClassificationFew-shot binary text classification with Induction Networks and Word2Vec weights initialization
Stars: ✭ 32 (-89.26%)
Multi Class Text Classification Cnn RnnClassify Kaggle San Francisco Crime Description into 39 classes. Build the model with CNN, RNN (GRU and LSTM) and Word Embeddings on Tensorflow.
Stars: ✭ 570 (+91.28%)
Sentiment analysis albertsentiment analysis、文本分类、ALBERT、TextCNN、classification、tensorflow、BERT、CNN、text classification
Stars: ✭ 61 (-79.53%)
ServenetService Classification based on Service Description
Stars: ✭ 21 (-92.95%)
Nlp Projectsword2vec, sentence2vec, machine reading comprehension, dialog system, text classification, pretrained language model (i.e., XLNet, BERT, ELMo, GPT), sequence labeling, information retrieval, information extraction (i.e., entity, relation and event extraction), knowledge graph, text generation, network embedding
Stars: ✭ 360 (+20.81%)
Lightnlp基于Pytorch和torchtext的自然语言处理深度学习框架。
Stars: ✭ 739 (+147.99%)
Text Classification DemosNeural models for Text Classification in Tensorflow, such as cnn, dpcnn, fasttext, bert ...
Stars: ✭ 144 (-51.68%)
RmdlRMDL: Random Multimodel Deep Learning for Classification
Stars: ✭ 375 (+25.84%)
Multi Class Text Classification CnnClassify Kaggle Consumer Finance Complaints into 11 classes. Build the model with CNN (Convolutional Neural Network) and Word Embeddings on Tensorflow.
Stars: ✭ 410 (+37.58%)
Product-Categorization-NLPMulti-Class Text Classification for products based on their description with Machine Learning algorithms and Neural Networks (MLP, CNN, Distilbert).
Stars: ✭ 30 (-89.93%)
Mobilenetv2A Keras implementation of MobileNetV2.
Stars: ✭ 277 (-7.05%)
social-cnn-pytorchHuman Trajectory Prediction in Socially Interacting Crowds Using a CNN-based Architecture
Stars: ✭ 24 (-91.95%)
DeepnetImplementation of CNNs, RNNs, and many deep learning techniques in plain Numpy.
Stars: ✭ 285 (-4.36%)
FfdnetFFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising (TIP, 2018)
Stars: ✭ 274 (-8.05%)
AskNowNQSA question answering system for RDF knowledge graphs.
Stars: ✭ 32 (-89.26%)
Pytorch Image ClassificationTutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.
Stars: ✭ 272 (-8.72%)
sibeExperimental Haskell machine learning library
Stars: ✭ 35 (-88.26%)
go2vecRead and use word2vec vectors in Go
Stars: ✭ 44 (-85.23%)
Image CaptioningImage Captioning using InceptionV3 and beam search
Stars: ✭ 290 (-2.68%)
Nlu simall kinds of baseline models for sentence similarity 句子对语义相似度模型
Stars: ✭ 286 (-4.03%)
Caffe HrtHeterogeneous Run Time version of Caffe. Added heterogeneous capabilities to the Caffe, uses heterogeneous computing infrastructure framework to speed up Deep Learning on Arm-based heterogeneous embedded platform. It also retains all the features of the original Caffe architecture which users deploy their applications seamlessly.
Stars: ✭ 271 (-9.06%)
Lbl2VecLbl2Vec learns jointly embedded label, document and word vectors to retrieve documents with predefined topics from an unlabeled document corpus.
Stars: ✭ 25 (-91.61%)
cadeCompass-aligned Distributional Embeddings. Align embeddings from different corpora
Stars: ✭ 29 (-90.27%)
Resnetcam KerasKeras implementation of a ResNet-CAM model
Stars: ✭ 269 (-9.73%)
game2vecTensorFlow implementation of word2vec applied on https://www.kaggle.com/tamber/steam-video-games dataset, using both CBOW and Skip-gram.
Stars: ✭ 62 (-79.19%)
TextUnderstandingTsetlinMachineUsing the Tsetlin Machine to learn human-interpretable rules for high-accuracy text categorization with medical applications
Stars: ✭ 48 (-83.89%)
Pytorch SaltnetKaggle | 9th place single model solution for TGS Salt Identification Challenge
Stars: ✭ 270 (-9.4%)
WeSTClass[CIKM 2018] Weakly-Supervised Neural Text Classification
Stars: ✭ 67 (-77.52%)
In PrestissimoA very fast neural network computing framework optimized for mobile platforms.QQ group: 676883532 【验证信息输:绝影】
Stars: ✭ 268 (-10.07%)
HiLAPCode for paper "Hierarchical Text Classification with Reinforced Label Assignment" EMNLP 2019
Stars: ✭ 116 (-61.07%)