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Deep Learning Time SeriesList of papers, code and experiments using deep learning for time series forecasting
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Multitask sentiment analysisMultitask Deep Learning for Sentiment Analysis using Character-Level Language Model, Bi-LSTMs for POS Tag, Chunking and Unsupervised Dependency Parsing. Inspired by this great article https://arxiv.org/abs/1611.01587
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ChicksexerA Python package for gender classification.
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Shapley regressionsStatistical inference on machine learning or general non-parametric models
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Stock Price PredictorThis project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.
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Keras LmuKeras implementation of Legendre Memory Units
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Pytorch Sentiment AnalysisTutorials on getting started with PyTorch and TorchText for sentiment analysis.
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Time-Series-ForecastingRainfall analysis of Maharashtra - Season/Month wise forecasting. Different methods have been used. The main goal of this project is to increase the performance of forecasted results during rainy seasons.
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Image CaptioningImage Captioning: Implementing the Neural Image Caption Generator with python
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StockpredictionPlain Stock Close-Price Prediction via Graves LSTM RNNs
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Document Classifier LstmA bidirectional LSTM with attention for multiclass/multilabel text classification.
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Rnn ctcRecurrent Neural Network and Long Short Term Memory (LSTM) with Connectionist Temporal Classification implemented in Theano. Includes a Toy training example.
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Robust-Deep-Learning-PipelineDeep Convolutional Bidirectional LSTM for Complex Activity Recognition with Missing Data. Human Activity Recognition Challenge. Springer SIST (2020)
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Stock Trading MlA stock trading bot that uses machine learning to make price predictions.
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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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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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Tensorflow Lstm SinTensorFlow 1.3 experiment with LSTM (and GRU) RNNs for sine prediction
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DeepseqslamThe Official Deep Learning Framework for Route-based Place Recognition
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Gdax Orderbook MlApplication of machine learning to the Coinbase (GDAX) orderbook
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SangitaA Natural Language Toolkit for Indian Languages
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Lstm Ctc Ocrusing rnn (lstm or gru) and ctc to convert line image into text, based on torch7 and warp-ctc
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Pytorch Pos TaggingA tutorial on how to implement models for part-of-speech tagging using PyTorch and TorchText.
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Char Rnn KerasTensorFlow implementation of multi-layer recurrent neural networks for training and sampling from texts
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Image Caption GeneratorA neural network to generate captions for an image using CNN and RNN with BEAM Search.
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Linear Attention Recurrent Neural NetworkA recurrent attention module consisting of an LSTM cell which can query its own past cell states by the means of windowed multi-head attention. The formulas are derived from the BN-LSTM and the Transformer Network. The LARNN cell with attention can be easily used inside a loop on the cell state, just like any other RNN. (LARNN)
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Image Caption Generator[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow
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Rnn Text Classification TfTensorflow Implementation of Recurrent Neural Network (Vanilla, LSTM, GRU) for Text Classification
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Pytorch Kaldipytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.
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Deep News SummarizationNews summarization using sequence to sequence model with attention in TensorFlow.
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handson-ml도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.
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LstmvisVisualization Toolbox for Long Short Term Memory networks (LSTMs)
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ConvLSTM-PyTorchConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST
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Machine Learning Is All You Need🔥🌟《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!💪 This repository is ALL You Need!
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Flow ForecastDeep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
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RwaMachine Learning on Sequential Data Using a Recurrent Weighted Average
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SentimentAnalysis(BOW, TF-IDF, Word2Vec, BERT) Word Embeddings + (SVM, Naive Bayes, Decision Tree, Random Forest) Base Classifiers + Pre-trained BERT on Tensorflow Hub + 1-D CNN and Bi-Directional LSTM on IMDB Movie Reviews Dataset
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Time AttentionImplementation of RNN for Time Series prediction from the paper https://arxiv.org/abs/1704.02971
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SequiturLibrary of autoencoders for sequential data
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Ner LstmNamed Entity Recognition using multilayered bidirectional LSTM
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Chainer Rnn NerNamed Entity Recognition with RNN, implemented by Chainer
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Getting Things Done With PytorchJupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.
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AC-VRNNPyTorch code for CVIU paper "AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction"
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unicornnOfficial code for UnICORNN (ICML 2021)
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