AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

2019新型冠状病毒疫情可视化。COVID-2019(原NCOV)，武汉(WuHan)疫情、全国疫情地图及时间轴变化，各省市地图及疫情曲线。疫情数据分析系统，疫情小区可视化，COVID-2019 Data Visualization Analysis System (前端+后端+数据清洗)

Nextstrain build for novel coronavirus (nCoV)

Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE

2019新型冠状病毒疫情时间序列数据仓库 | COVID-19/2019-nCoV Infection Time Series Data Warehouse

Context From World Health Organization - On 31 December 2019, WHO was alerted to several cases of pneumonia in Wuhan City, Hubei Province of China. The virus did not match any other known virus. Th…

针对新冠病毒疫情数据的清洗脚本和清洗后的数据，数据源使用 https://github.com/BlankerL/DXY-COVID-19-Data 的每日抓取数据

I am a full-stack engineer for AI projects, glad to share my experience. pratices make the top engineer.

This repo holds the code for crawling the latest news on the pneumonia virus from the Internet

武汉2019新型冠状病毒疫情可视化(全国疫情地图及时间轴变化)

Repository containing lectures from 2020 Machine Learning course at Skoltech

Novel Coronavirus SARS-CoV-2 (2019-nCoV) Italian Outbreak Data Repository

最良心的 Python 教程：

【已发布弹幕版本，大家不要搞坏了！新版大屏beta 版本，全实时数据，交互式大屏，精确到城市级，弹幕来袭】关注2019新型冠状病毒（2019-nCoV），数据可视化感染人群热点图、迁徙扩散轨迹，以提供帮助分析疫情。 愿世界安好。Focus on Wuhan 2019-nCoV, data visualization, to help analyze the epidemic situatio…

An Open Source Machine Learning Framework for Everyone

Python脚本。模拟登录知乎， 爬虫，操作excel，微信公众号，远程开机

新型冠状病毒疫情数据三维可视化

Set of real world data science tasks completed using the Python Pandas library

李宏毅《机器学习》笔记，在线阅读地址：https://datawhalechina.github.io/leeml-notes

Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html

Logistic regression from scratch in Python

台湾大学李宏毅老师机器学习

Jupyter Notebook & Data Associated with my Tutorial video on the Python NumPy Library

Source code to go along with my tutorial to learn data visualization with the matplotlib library of Python

An implementation of Cascade R-CNN: Delving into High Quality Object Detection.

TensorFlow Tutorial for Data Scientist

1st place solution of Deep Learning Beginner Challenge

Convolutional Neural Networks