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rnn-tensorflow
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Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.
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Jan 10, 2019 - Python
Char-RNN implemented using TensorFlow.
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Mar 29, 2018 - Python
Little More Advanced TensorFlow Implementations
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Nov 29, 2017 - Jupyter Notebook
Implementing Recurrent Neural Network from Scratch
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May 28, 2018 - Python
Source code of CHAMELEON - A Deep Learning Meta-Architecture for News Recommender Systems
deep-neural-networks
deep-learning
tensorflow
word2vec
word-embeddings
lstm
rnn
recommendation-system
recommendation-engine
recommender-system
recommendation-algorithms
rnn-tensorflow
lstm-neural-networks
lstm-neural-network
news-recommendation
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Dec 8, 2019 - Python
Chinese Poetry Generation
poetry
lstm
rnn
seq2seq
beam-search
attention-mechanism
rnn-tensorflow
seq2seq-model
poetry-generator
rnn-encoder-decoder
bidirectional-lstm
chinese-poetry
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Sep 9, 2017 - Jupyter Notebook
Char-level RNN LSTM text generator📄 .
python
machine-learning
text-mining
ai
deep-learning
artificial-intelligence
lstm
rnn
rnn-tensorflow
lstm-neural-networks
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Jul 24, 2019 - Python
Macklemoreh
commented
Mar 28, 2020
new_lstm = eidetic_lstm(
name='e3d' + str(i),
input_shape=[ims_width, window_length, ims_height, num_hidden_in],
output_channels=num_hidden[i],
kernel_shape=[2, 5, 5])
Should the input_shape be [window_length, ims_width, ims_height, num_hidden_in]?
[ICMLC 2018] A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection
machine-learning
tensorflow
svm
recurrent-neural-networks
artificial-intelligence
gru
supervised-learning
classification
intrusion-detection
rnn
artificial-neural-networks
support-vector-machine
rnn-tensorflow
svm-classifier
softmax
classification-task
gru-svm
gru-model
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May 22, 2020 - Python
This was my Master's project where i was involved using a dataset from Wireless Sensor Data Mining Lab (WISDM) to build a machine learning model to predict basic human activities using a smartphone accelerometer, Using Tensorflow framework, recurrent neural nets and multiple stacks of Long-short-term memory units(LSTM) for building a deep network. After the model was trained, it was saved and exported to an android application and the predictions were made using the model and the interface to speak out the results using text-to-speech API.
machine-learning
deep-learning
proof-of-concept
scikit-learn
android-application
python3
pickle
rnn-tensorflow
androidstudio
lstm-neural-networks
pycharm-ide
human-activities
hidden-units
smartphone-accelerometer
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Sep 25, 2017 - Python
Char-level RNN LSTM password cracker 🔑 🔓 .
python
machine-learning
text-mining
ai
deep-learning
password-generator
hacking
password
recurrent-neural-networks
artificial-intelligence
lstm
neural-networks
rnn
rnn-tensorflow
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Jul 24, 2019
Deep Learning neural network for correcting spelling
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Mar 30, 2020 - Python
Hands-On Deep Learning Algorithms with Python, By Packt
python
machine-learning
deep-learning
deep-learning-algorithms
rnn-tensorflow
cnn-architecture
cycle-gan
capsule-network
few-shot-learning
stack-gan
tensorflow-2
nadam
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Aug 27, 2019 - Jupyter Notebook
Recurrent Neural Network (LSTM) by using TensorFlow and Keras in Python for BitCoin price prediction
python
neural-network
bitcoin
keras
prediction
cnn
rnn
deeplearning
rnn-tensorflow
keras-neural-networks
rnn-model
keras-tensorflow
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Feb 27, 2018 - Python
Predict stock movement with Machine Learning and Deep Learning algorithms
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Dec 5, 2018 - Jupyter Notebook
Implementation of the methods proposed in **Adversarial Training Methods for Semi-Supervised Text Classification** on IMDB dataset (without pre-training)
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May 9, 2018 - Jupyter Notebook
Voice Activity Detection LSTM-RNN learning model
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Apr 17, 2018 - Python
The implementation of LSTM in TensorFlow used for the stock prediction.
machine-learning
deep-learning
tensorflow
stock-price-prediction
rnn-tensorflow
lstm-neural-networks
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Jan 7, 2020 - Jupyter Notebook
Generating Music and Lyrics using Deep Learning via Long Short-Term Recurrent Networks (LSTMs). Implements a Char-RNN in Python using TensorFlow.
machine-learning
deep-neural-networks
deep-learning
creative-coding
music-generation
rnn-tensorflow
lstm-neural-networks
kadenze
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Jul 21, 2017 - Jupyter Notebook
A siamese LSTM to detect sentence/question pairs.
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Oct 21, 2017 - Python
Generating Pokemon cards using a mixture of StyleGAN and RNN to create beautiful & vibrant cards ready for battle!
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Jan 29, 2020 - Python
TensorFlow implementations of several deep learning models (e.g. variational autoencoder, RNN, ...)
python
machine-learning
deep-learning
notebook
tensorflow
cnn
recurrent-neural-networks
ipynb
rnn
vae
convolutional-neural-networks
convolutional-neural-network
rnn-tensorflow
variational-autoencoder
recurrent-neural-network
cnn-tensorflow
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Jun 26, 2018 - Jupyter Notebook
The first AI-based Arabic songwriter.
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Apr 7, 2017 - Jupyter Notebook
TensorFlow implementation of Graphical Attention Recurrent Neural Networks based on work by Cirstea et al., 2019.
tensorflow
shape
batch
rnn
attention
attention-mechanism
rnn-tensorflow
graph-convolutional-networks
temporal-data
paper-implementations
graph-signals
graph-neural-networks
diffusion-graph-convolution
attention-matrix
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Jan 2, 2020 - Python
A Twitter bot powered by a Recurrent Neural Network (RNN)
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Oct 21, 2017 - Python
Deep Learning notes and practical implementation with Tensorflow and keras. Text Analytics and practical application implementation with NLTK, Spacy and Gensim.
python
tensorflow
lstm
rnn
image-recognition
tensorboard
recommender-system
deeplearning
rnn-tensorflow
nlp-machine-learning
opencv-python
rnn-model
keras-tensorflow
gensim-word2vec
spacy-nlp
yolov3
rnn-gru
rnn-lstm
rnn-keras
kers
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Sep 18, 2019 - Jupyter Notebook
Inspired by the neural style algorithm in the computer vision field, we propose a high-level language model with the aim of adapting the linguistic style.
tensorflow
generative-model
rnn
vae
tensorflow-experiments
rnn-tensorflow
tensorflow-models
rnn-encoder-decoder
vrae
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Jul 18, 2017 - Jupyter Notebook
Reproducing the results of the paper "Bayesian Recurrent Neural Networks" by Fortunato et al.
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Mar 30, 2018 - Jupyter Notebook
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I looked up the documentation for sequence_loss_by_example and it doesn't seem to be taking vocab_size as argument. I'd really appreciate it if you could help me understand what this argument is doing. Thanks a lot!
` loss = seq2seq.sequence_loss_by_example([self.logits],
[tf.reshape(self.targets, [-1])],
[tf.ones([args.batch_size * args.seq_length])],