LSTMs are useful for building character-sequential prediction models. In this project, string scoring models were built using LSTMs and a language detector was built upon them.
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Updated
Jul 11, 2017 - Jupyter Notebook
LSTMs are useful for building character-sequential prediction models. In this project, string scoring models were built using LSTMs and a language detector was built upon them.
Solve simple contest problems with ML
Rnn (vanial, GRU and LSTM) from scratch
This is a practical implementation implementing neural networks on top of fasttext as well as word2vec word embeddings.
Source Code Generation Based On User Intention Using LSTM Networks
A simple LSTM network to predict bitcoin closing prices
LSTM Sentiment Analysis
Statistical Analysis on E-Commerce Reviews, with Sentiment Classification using Bidirectional Recurrent Neural Network (RNN)
Time-series prediction with LSTNet in Apache MXNet Gluon
Large-scale Exploration of Neural Relation Classification Architectures
Named Entity Recognition - Python - Keras
Train a Long-Short Term Memory neural network to write the Poetry of Tang Dynasty
LSTM Network from Scratch in C++
Deep Neural Network based web page classifier - LSTM, GloVe, SVM, Naive Bayes
generate Simpsons TV scripts using RNNs.
Image classification using CNN
Leverage the power of Keras to build and train state-of-the-art deep learning models
Building a Recurrent Neural Network Step by Step
Prediction of a star light curve behaviour with a neural network
LSTM neural network to identify textual entailment
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