pengchen233's repositories
numpy-study
how to use numpy in nn
TensorFlow-Course
Simple and ready-to-use tutorials for TensorFlow
EEMD-LSTM-Model
基于深度学习的溶解氧时间序列预测模型
algorithm-visualizer
:fireworks:Interactive Online Platform that Visualizes Algorithms from Code
LSTM
时间序列预测
dimensionality_reduction_alo_codes
特征提取/数据降维:PCA、LDA、MDS、LLE、TSNE等降维算法的python实现
PyTorchDocs
PyTorch 官方中文教程包含 60 分钟快速入门教程，强化教程，计算机视觉，自然语言处理，生成对抗网络，强化学习。欢迎 Star，Fork！
SP_Lib
Signal processing method and algorithm library
vae
a simple vae and cvae from keras
attention
some attention implements
SWLSTM_GPR
A new probabilistic wind speed prediction method, called Shared Weight Long Short-Term Memory Network combined with Gaussian Process Regression
AE_ts
Auto encoder for time series
HyperDL-Tutorial
深度学习教程整理 | 干货
MachineLearning
Basic Machine Learning and Deep Learning
python-machine-learning-book
The "Python Machine Learning (1st edition)" book code repository and info resource
naacl_transfer_learning_tutorial
Repository of code for the tutorial on Transfer Learning in NLP held at NAACL 2019 in Minneapolis, MN, USA
cqr
Conformalized Quantile Regression
Time-Series-ARIMA-XGBOOST-RNN
Time series forecasting for individual household power prediction: ARIMA, xgboost, RNN
QRMGM_KDE
A probabilistic forecasting method based on Quantile Regression Minimal Gated Memory Network and Kernel Density Estimation.
PSO-vs-WOA
The Matlab/Octave code contains codes of Whale Optimization Algorithm and Particle Swarm Optimization.
ewtpy
Empirical Wavelet Transform Python implementation
Summer-Research-2018-Part-One
PART I DeepAR implementation based on paper: https://arxiv.org/pdf/1704.04110.pdf
GBDT_Simple_Tutorial
python实现GBDT的回归、二分类以及多分类，将算法流程详情进行展示解读并可视化，庖丁解牛地理解GBDT。Gradient Boosting Decision Trees regression, dichotomy and multi-classification are realized based on python, and the details of algorithm flow are displayed, interpreted and visualized to help readers better understand Gradient Boosting Decision Trees
MachineLearning-1
Machine Learning in Action学习笔记，一个文件夹代表一个算法，每个文件夹包含算法所需的数据集、源码和图片，图片放在pic文件夹中，数据集放在在Data文件夹内。书中的代码是python2的，有不少错误，这里代码是我用python3写的，且都能直接运行
kvae
Kalman Variational Auto-Encoder
LSTNet_keras
Keras version of LSTNet
Spatial-Statistics
The repository contains methods and applications of spatial-statistics, like Fast and Adaptive Kernel Density Estimation for Hundreds of Millions of points
WLSSVM_python
Weighted LSSVM for regression