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Deep Trading AgentDeep Reinforcement Learning based Trading Agent for Bitcoin
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spikeRNNNo description or website provided.
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ArtificioDeep Learning Computer Vision Algorithms for Real-World Use
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LayerNeural network inference the Unix way
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Predrnn PytorchOfficial implementation for NIPS'17 paper: PredRNN: Recurrent Neural Networks for Predictive Learning Using Spatiotemporal LSTMs.
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Reinvent RandomizedRecurrent Neural Network using randomized SMILES strings to generate molecules
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Entity Relation ExtractionEntity and Relation Extraction Based on TensorFlow and BERT. 基于TensorFlow和BERT的管道式实体及关系抽取,2019语言与智能技术竞赛信息抽取任务解决方案。Schema based Knowledge Extraction, SKE 2019
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dl-reluDeep Learning using Rectified Linear Units (ReLU)
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OCROptical character recognition Using Deep Learning
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CtcdecoderConnectionist Temporal Classification (CTC) decoding algorithms: best path, prefix search, beam search and token passing. Implemented in Python.
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PathNRESource code and dataset of EMNLP2017 paper "Incorporating Relation Paths in Neural Relation Extraction".
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sequence-rnn-pySequence analyzing using Recurrent Neural Networks (RNN) based on Keras
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Faced🚀 😏 Near Real Time CPU Face detection using deep learning
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DeepSegmentorSequence Segmentation using Joint RNN and Structured Prediction Models (ICASSP 2017)
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entity-networkTensorflow implementation of "Tracking the World State with Recurrent Entity Networks" [https://arxiv.org/abs/1612.03969] by Henaff, Weston, Szlam, Bordes, and LeCun.
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FewrelA Large-Scale Few-Shot Relation Extraction Dataset
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regulatory-predictionCode and Data to accompany "Dilated Convolutions for Modeling Long-Distance Genomic Dependencies", presented at the ICML 2017 Workshop on Computational Biology
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VERSEVancouver Event and Relation System for Extraction
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Knowledge Graph LearningA curated list of awesome knowledge graph tutorials, projects and communities.
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knodleA PyTorch-based open-source framework that provides methods for improving the weakly annotated data and allows researchers to efficiently develop and compare their own methods.
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EfficientnasTowards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search https://arxiv.org/abs/1807.06906
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Vnet.pytorchA PyTorch implementation for V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
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datastories-semeval2017-task6Deep-learning model presented in "DataStories at SemEval-2017 Task 6: Siamese LSTM with Attention for Humorous Text Comparison".
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Wbc segmentaionWhite Blood Cell Image Segmentation Using Deep Convolution Neural Networks
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Tensorflow BookAccompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
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brunoa deep recurrent model for exchangeable data
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finfinance
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AggcnAttention Guided Graph Convolutional Networks for Relation Extraction (authors' PyTorch implementation for the ACL19 paper)
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TextclassificationAll kinds of neural text classifiers implemented by Keras
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