wywwgk's Stars
jaungiers/LSTM-Neural-Network-for-Time-Series-Prediction
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
lyhue1991/eat_tensorflow2_in_30_days
Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋
yajunpeng/Earthquake-Early-Warning
Improving EEW system performance with machine learning and convolutional neural network.
SongDark/cnn_autoencoder_mnist
CNN auto-encoder on mnist.
fedden/umap_tsne_embedding_visualiser
deeplearning-ai/machine-learning-yearning-cn
Machine Learning Yearning 中文版 - 《机器学习训练秘籍》 - Andrew Ng 著
baidu/Curve
An Integrated Experimental Platform for time series data anomaly detection.
locuslab/TCN
Sequence modeling benchmarks and temporal convolutional networks
sherlockchou86/websocketj
redirect the STDIN/STDOUT from server side to web browser. you can operate/monitor the server side program in browser. written by Java language.
beamandrew/deep_learning_works
Code to accompany "You can probably use deep learning even if your data isn't that big" blog post
eqcorrscan/EQcorrscan
Earthquake detection and analysis in Python.
facebookresearch/fairseq-lua
Facebook AI Research Sequence-to-Sequence Toolkit
hzy46/TensorFlow-Time-Series-Examples
Time Series Prediction with tf.contrib.timeseries
caicloud/tensorflow-tutorial
Example TensorFlow codes and Caicloud TensorFlow as a Service dev environment.
MorvanZhou/Tensorflow-Tutorial
Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学
exacity/deeplearningbook-chinese
Deep Learning Book Chinese Translation
curiousily/TensorFlow-on-Android-for-Human-Activity-Recognition-with-LSTMs
iPython notebook and Android app that shows how to build LSTM model in TensorFlow and deploy it on Android
wywwgk/deep-learning-HAR
Convolutional and LSTM networks to classify human activity
guillaume-chevalier/LSTM-Human-Activity-Recognition
Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier
sunshineatnoon/stanford_dl_ex
Programming exercises for the Stanford Unsupervised Feature Learning and Deep Learning Tutorial
sunshineatnoon/Single-Layer-CNN-on-MNIST
A single Layer CNN on MIST, get an acurray of 97.24%
chenjoya/Vehicle_Detection_Recognition
This is a Matlab lesson design for vehicle detection and recognition. Using cifar-10Net to training a RCNN, and finetune AlexNet to classify. Thanks to Cars Dataset:http://ai.stanford.edu/~jkrause/cars/car_dataset.html