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question-pairA siamese LSTM to detect sentence/question pairs.
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totally humansrnn trained on r/totallynotrobots 🤖
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ThesemicolonThis repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.
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TelemanomA framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.
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SpeakerDiarization RNN CNN LSTMSpeaker Diarization is the problem of separating speakers in an audio. There could be any number of speakers and final result should state when speaker starts and ends. In this project, we analyze given audio file with 2 channels and 2 speakers (on separate channels).
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sequence-rnn-pySequence analyzing using Recurrent Neural Networks (RNN) based on Keras
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myDLDeep Learning
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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.
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AilearningAiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP
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DeepseqslamThe Official Deep Learning Framework for Route-based Place Recognition
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time-series-forecasting-tensorflowjsPull stock prices from online API and perform predictions using Long Short Term Memory (LSTM) with TensorFlow.js framework
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RnnsharpRNNSharp is a toolkit of deep recurrent neural network which is widely used for many different kinds of tasks, such as sequence labeling, sequence-to-sequence and so on. It's written by C# language and based on .NET framework 4.6 or above versions. RNNSharp supports many different types of networks, such as forward and bi-directional network, sequence-to-sequence network, and different types of layers, such as LSTM, Softmax, sampled Softmax and others.
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BasicocrBasicOCR是一个致力于解决自然场景文字识别算法研究的项目。该项目由长城数字大数据应用技术研究院佟派AI团队发起和维护。
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Lstm Human Activity RecognitionHuman Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier
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Video ClassificationTutorial for video classification/ action recognition using 3D CNN/ CNN+RNN on UCF101
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Ad examplesA collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
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DeeptradeA LSTM model using Risk Estimation loss function for stock trades in market
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