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adversarial

Code and hyperparameters for the paper "Generative Adversarial Networks"

algorithm_example

algorithms

An educational library of algorithms in Python

algorithms-1

全面的算法代码仓库

algorithms-2

Minimal examples of data structures and algorithms in Python

awesome-tensorflow

TensorFlow - A curated list of dedicated resources http://tensorflow.org

chatroom

A Erogenous Chatroom by Python.

computer-vision-action

computer vision learning, include python machine learning action(sklearn); machinelearningaction; Computer vision based on deep learning ;Coursera_deeplearning.ai and other cv learning materials...

datastruct

数据结构(C语言实现)

deeplearning.ai

deeplearning.ai , By Andrew Ng, All slide and notebook + code and some material.

deeplearning_ai_books

deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）

deeplearning_ng

esp8266_deauther

ESP8266 deauther

face_recognition

Using PCA to reduce the face features' dimension and using SVM ( & KNN) to classify.

facial-expression-recognition

Facial-Expression-Recognition in TensorFlow. Detecting faces in video and recognize the expression(emotion).

fcn.berkeleyvision.org

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.

ican

Instance centric attention network is being implemented by pytorch.

interview-notebook

:books: 技术面试需要掌握的基础知识整理，欢迎编辑~

interviews

Everything you need to know to get the job.

jpeg-encoder

JPEG implemention

lauz.github.io

MY BLOG

linux

Linux kernel source tree

machinelearning

Machine Learning in Action（机器学习实战）

machinelearning-1

周志华《机器学习》

machinelearning_ng

吴恩达机器学习coursera课程，学习代码(2017年秋) The Stanford Coursera course on MachineLearning with Andrew Ng

ml_algorithms

prml

PRML algorithms implemented in Python

py-faster-rcnn

Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version

python-cookbook

some code in python cookcode

restricted-boltzmann-machine

to implement RBM introduced in <<Reducing the Dimensionality of Data with Neural Networks>>