PyTorch implementation of Neural Turing Machine recurrent neural network
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Updated
Nov 2, 2019 - Python
PyTorch implementation of Neural Turing Machine recurrent neural network
Application of LSTM networks and modified RNN cells to various Time Series Classification problems
Implementation of a Recurrent Neural Network with LSTM cells, in pure Python.
Twitter data on US Airlines Sentiment Analysis with Deep Learning (LSTM and CNN)
This repo includes Zhang2019's CLSTM implemented using keras(tensorflow2). Zhang2019:Zhang, Haokui, et al. "Exploiting temporal consistency for real-time video depth estimation." Proceedings of the IEEE International Conference on Computer Vision. 2019.
A LSTM implementation with only using basic components of pytorch
Generates shakespeare style play by LSTM (RNN) network.
Image captioning
Text generation using a character-based RNN with LSTM cells. We will work with a dataset of Shakespeare's writing from Andrej Karpathy's The Unreasonable Effectiveness of Recurrent Neural Networks. Given a sequence of characters from this data ("Shakespear"), train a model to predict the next character in the sequence ("e"). Longer sequences of …
Sentiment Classifier using a bidirectional stacked RNN with LSTM/GRU cells for the Twitter sentiment analysis dataset
Yeezy Taught Me Text Generation. Training next character predictions RNN LSTM model with user input text corpus
Implemented Convolutional Neural Network, LSTM Neural Network, and Neural Network From Scratch in Python Language.
This is a project implementing Computer Vision and Deep Learning concepts to detect drowsiness of a driver and sound an alarm if drowsy.
Language Modeling
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