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autoencoder

Text autoencoder with LSTMs

autoencoder-1

LSTM autoencoder for sentence embedding generation

bmm_attentional_cnn

A CNN with an attentional module that I built while attending the brains minds and machines summer course

caffe2

Caffe2 is a lightweight, modular, and scalable deep learning framework.

code

dbse-monitor

deep-learning-time-series-prediction-using-lstm-recurrent-neural-networks

This project aims to predict VOLATILITY S&P 500 (^VIX) time series using LSTM.

deeplearning-timeseries

Timeseries Forecasting via Recurrent Neural Nets [Keras + Theano]

deepst

Deep Learning for Spatio-Temporal Data

fusenet

Deep fusion project of deeply-fused nets, and the study on the connection to ensembling

gan_anomaly

anomaly detection with GAN

gigers_lstm

(machine learning) Unsupervised learning models for text: 1. LSTM Language Model 2. LSTM Autoencoder

giraf

MATLAB implementation of the GIRAF algorithm for convolutional structured low-rank matrix recovery

gpu-krls

GPU implementaion of Kernel Recursive Least Squares (KRLS) algorithm

grasp-and-lift-eeg-challenge

Code and documentation for the winning sollution to the Grasp-and-Lift EEG Detection challenge

group-anomaly-detection-with-bayesian-network

ijcai-18-alimama-search-conversion-rate-cvr-prediction-contest

This is my code for IJCAI-18 CVR Prediction Contest

keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano.

keras_lstm_vae

Keras implementation of LSTM Variational Autoencoder

lstm-autoencoder

TensorFlow LSTM-autoencoder implementation

lstm-autoencoder-1

LSTM based Autoencoder for extracting high-level representations from sequential categorical data

lstm-matlab

LSTM-MATLAB is Long Short-term Memory (LSTM) in MATLAB, which is meant to be succinct, illustrative and for research purpose only. It is accompanied with a paper for reference: Revisit Long Short-Term Memory: An Optimization Perspective, NIPS deep learning workshop, 2014.

ml_for_hackers

Code accompanying the book "Machine Learning for Hackers"

mlhackers

neural-network-with-financial-time-series-data

This solution presents an accessible, non-trivial example of machine learning (Deep learning) with financial time series using Keras on top of Tensor Flow

nmt.matlab

Code to train state-of-the-art Neural Machine Translation systems.

ospabp

OSPABP: UAV flight data anomaly detection based on oversampling projection approximation basis pursuit

prontodata

Scripts to Analyze Pronto's Data Release

python-machine-learning-book

The "Python Machine Learning" book code repository and info resource

recurent_autoencoder_temp_model

We want to force temporal models, like LSTM and GRU, to have better representation of the past (better memory). We do this by reconstructing the previous hidden representations using autoencoders.