Deep Learning Time SeriesList of papers, code and experiments using deep learning for time series forecasting
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Gdax Orderbook MlApplication of machine learning to the Coinbase (GDAX) orderbook
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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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Pytorch Sentiment AnalysisTutorials on getting started with PyTorch and TorchText for sentiment analysis.
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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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Image Caption Generator[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow
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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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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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Up Down CaptionerAutomatic image captioning model based on Caffe, using features from bottom-up attention.
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Pytorch Seq2seqTutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
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dtsA Keras library for multi-step time-series forecasting.
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tiny-rnnLightweight C++11 library for building deep recurrent neural networks
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Da Rnn📃 **Unofficial** PyTorch Implementation of DA-RNN (arXiv:1704.02971)
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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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Carrot🥕 Evolutionary Neural Networks in JavaScript
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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.
Stars: ✭ 277 (-71.12%)
ZhihuThis repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.
Stars: ✭ 3,307 (+244.84%)
Coursera Deep Learning SpecializationNotes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
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Screenshot To CodeA neural network that transforms a design mock-up into a static website.
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StylenetA cute multi-layer LSTM that can perform like a human 🎶
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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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CS231nPyTorch/Tensorflow solutions for Stanford's CS231n: "CNNs for Visual Recognition"
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sgrnnTensorflow implementation of Synthetic Gradient for RNN (LSTM)
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sequence-rnn-pySequence analyzing using Recurrent Neural Networks (RNN) based on Keras
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Image CaptioningImage Captioning using InceptionV3 and beam search
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QtraderReinforcement Learning for Portfolio Management
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Stock Prediction ModelsGathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
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Deep learning nlpKeras, PyTorch, and NumPy Implementations of Deep Learning Architectures for NLP
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Ner LstmNamed Entity Recognition using multilayered bidirectional LSTM
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Video ClassificationTutorial for video classification/ action recognition using 3D CNN/ CNN+RNN on UCF101
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ThesemicolonThis repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.
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Pytorch NtmNeural Turing Machines (NTM) - PyTorch Implementation
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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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Qa RankitQA - Answer Selection (Rank candidate answers for a given question)
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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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