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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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question-pairA siamese LSTM to detect sentence/question pairs.
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Sequence-Models-courseraSequence Models by Andrew Ng on Coursera. Programming Assignments and Quiz Solutions.
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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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Rnn Theano使用Theano实现的一些RNN代码,包括最基本的RNN,LSTM,以及部分Attention模型,如论文MLSTM等
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Seq2seq ChatbotChatbot in 200 lines of code using TensorLayer
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tf-ran-cellRecurrent Additive Networks for Tensorflow
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DeepseqslamThe Official Deep Learning Framework for Route-based Place Recognition
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sequence-rnn-pySequence analyzing using Recurrent Neural Networks (RNN) based on Keras
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deep-transTransliterating English to Hindi using Recurrent Neural Networks
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DrowsyDriverDetectionThis is a project implementing Computer Vision and Deep Learning concepts to detect drowsiness of a driver and sound an alarm if drowsy.
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myDLDeep Learning
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ConvLSTM-PyTorchConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST
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CS231nMy solutions for Assignments of CS231n: Convolutional Neural Networks for Visual Recognition
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dltfHands-on in-person workshop for Deep Learning with TensorFlow
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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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Video ClassificationTutorial for video classification/ action recognition using 3D CNN/ CNN+RNN on UCF101
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tiny-rnnLightweight C++11 library for building deep recurrent neural networks
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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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lstm harLSTM based human activity recognition using smart phone sensor dataset
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totally humansrnn trained on r/totallynotrobots 🤖
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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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