wywywy01's repositories
Algorithms
The codes and my solutions to exercises from the book "Algorithms" (4th edition) by Robert Sedgewick and Kevin Wayne.
awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
machinelearninginaction-master
python_machine_learning_shizhan
pyscatwave
Fast Scattering Transform with CuPy/PyTorch
AdversarialNetsPapers
The classical papers and codes about generative adversarial nets
algs4
Algorithms, 4th edition textbook code and libraries
Bilinear-CNN-TensorFlow
This is an implementation of Bilinear CNN using TensorFlow.
caffe
Caffe: a fast open framework for deep learning.
caffe-heatmap
Caffe with heatmap regression & spatial fusion layers. Useful for any CNN image position regression task.
DeepLearningTutorial
Deep learning tutorial in Chinese/深度学习教程中文版
django
The Web framework for perfectionists with deadlines.
edx-documentation
For published versions of the edX documentation, visit:
MachineLearning_python
source_code
Multilabel-timeseries-classification-with-LSTM
Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks.
my-edx
share docs
pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
pandas_exercises
Practice your pandas skills!
papaa-opencl
OpenCL Labs for PAPAA Summer School 2016 Edition
pmtk3
Probabilistic Modeling Toolkit for Matlab/Octave.
pose-hg-train
Training and experimentation code used for "Stacked Hourglass Networks for Human Pose Estimation"
PRMLT
Matlab code for algorithms in PRML book
residual-attention-network
Residual Attention Network for Image Classification
RNNSharp
RNNSharp is a toolkit of deep recurrent neural network which is widely used for many different kinds of tasks, such as sequence labeling, sequence-to-sequence and so on. It's written by C# language and based on .NET framework 4.6 or above versions. RNNSharp supports many different types of networks, such as forward and bi-directional network, sequence-to-sequence network, and different types of layers, such as LSTM, Softmax, sampled Softmax and others.
scikit-learn
scikit-learn: machine learning in Python
sklearn-pandas
Pandas integration with sklearn
t_pi
dd
Tencent2017_Final_Coda_Allegro
腾讯2017社交广告源码（决赛排名第23位）
vehicle-detection
Created vehicle detection pipeline with two approaches: (1) deep neural networks (YOLO framework) and (2) support vector machines ( OpenCV + HOG).
xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow