cnzero

fucking-algorithm

刷算法全靠套路，认准 labuladong 就够了！English version supported! Crack LeetCode, not only how, but also why.

frp

A fast reverse proxy to help you expose a local server behind a NAT or firewall to the internet.

DeepLearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06

you-get

:arrow_double_down: Dumb downloader that scrapes the web

deeplearning-models

A collection of various deep learning architectures, models, and tips

conv_arithmetic

A technical report on convolution arithmetic in the context of deep learning

machine-learning-systems-design

A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems"

Interview

Interview = 简历指南 + 算法题 + 八股文 + 源码分析

MNN

MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba

tsfresh

Automatic extraction of relevant features from time series:

cnn-explainer

Learning Convolutional Neural Networks with Interactive Visualization.

deep-learning-coursera

Deep Learning Specialization by Andrew Ng on Coursera.

k-vim

vim配置

pytorch-template

PyTorch deep learning projects made easy.

deep-learning-roadmap

:satellite: All You Need to Know About Deep Learning - A kick-starter

tips_for_interview

我的一些面试心得；自学CS历程分享；找工作求职经验分享

awesome_time_series_in_python

This curated list contains python packages for time series analysis

machine-learning-yearning

Translation of <Machine Learning Yearning> by Andrew NG

BioSPPy

Biosignal Processing in Python

XJTU-Share

西安交通大学课程资料共享计划

automl_service

Deploy AutoML as a service using Flask

myo-raw

ICASSP2019_TCN

Improved sEMG-based gesture recognition

PythonMyoLinux

Gather sEMG/IMU data from Myo armbands, and obtain real time predictions.

Open-Myo

Python module to get data from a Myo armband using a generic BLE interface

EMG-Movement-Recognition

The source code for the the manuscript titled [M. AbdelMaseeh, T. W. Chen and D. W. Stashuk, "Extraction and Classification of Multichannel Electromyographic Activation Trajectories for Hand Movement Recognition," in IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 24, no. 6, pp. 662-673, June 2016.]. The paper proposes a system for hand movement recognition using multi-channel electromyographic (EMG) signals obtained from the forearm surface. This system can be potentially used to control prostheses or to provide input to a wide range of human computer interface systems. The developed methods were tested with the publicly available NINAPro database.

pyvicon

Python 3 wrapper over Vicon DataStream SDK (1.7.0 +)

intzeros.github.io

A minimal two-column Jekyll theme, based on bootstrap 3.

DeepLearning_Datasets_Models

Leet-three-idiots-Code

LeetCode Solutions and Discussions