sunssh Goto Github PK

functional-data-analysis

gemfield

Gemfield homework or libgemfield.so

generative-adversarial-network-tutorial

Tutorial on creating your own GAN in Tensorflow

gitskills

gittut

gluon-tutorials-zh

通过MXNet/Gluon来动手学习深度学习

gwnn

A TensorFlow implementation of Graph Wavelet Neural Network

har-keras-cnn

har-keras-coreml

Human Activity Recognition (HAR) with Keras and CoreML

har-stacked-residual-bidir-lstms

Using deep stacked residual bidirectional LSTM cells (RNN) with TensorFlow, we do Human Activity Recognition (HAR). Classifying the type of movement amongst 6 categories or 18 categories on 2 different datasets.

hctsa

Highly comparative time-series analysis code repository

hello-algorithm

🌍「算法面试+算法知识」针对小白的算法训练 | 还包括：1、阿里、字节、滴滴 百篇大厂面经汇总 2、千本开源电子书 3、百张思维导图 （右侧来个 star 吧 🌹，English version supported）

hello-world

first project

human-activity-recognition-using-cnn

Convolutional Neural Network for Human Activity Recognition in Tensorflow

human-behavior-recognition

Human behavior recognition,CNN

javaguide

「Java学习+面试指南」一份涵盖大部分Java程序员所需要掌握的核心知识。

javalearn

迷你版java面试笔试总结，不含图片，2w+字，面向有基础的同学，涵盖基础知识、框架、网络及中间件知识点总结，特殊场景处理，继续更新中。

kaggle

Kaggle 项目实战（教程） = 文档 + 代码 + 视频

keras

Deep Learning for humans

learn_dl

Deep learning algorithms source code for beginners

libsvm

libsvm_action

《机器学习》基于SVM的行为识别案例解析

lstm-human-activity-recognition

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN (Deep Learning algo). Classifying the type of movement amongst six activity categories - Guillaume Chevalier

models

Models and examples built with TensorFlow

motion-sense

MotionSense Dataset ( time-series data generated by smartphone's sensors: accelerometer and gyroscope)

mygittest

test

neural-networks-and-deep-learning

neurobiologically-plausible-behavioral-prediction

A model of mixed neural networks for step-by-step processing of dynamic visual scenes, activity recognition and behavioral prediciton

notebooks

my-deeplearning-practice-notebooks

orl_faces

ORL人脸识别不同算法的实现，用到了scikit-learn,tensorflow等，任选5张训练，5张测试。因为每次训练随机挑选，所以每次输出识别率有偏差 算法 识别率 bp神经网络 0.8 pca+bp神经网络 0.85 小波变换+pca+bp神经网络 0.95 CNN 0.98 小波变换+pca+SVM 0.98####同时希望大家提出宝贵意见，欢迎学习交流，如果你喜欢该项目，请star或者fork一下，你的主动将是我前行的动力####