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ailearning

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

attacks_on_complex_networks

In this work, we examine the resilience of two complex network types (Erdos Renyi, and Power-Law/Scale-free) to potential delivered attacks and random errors.

awesome-network-analysis

A curated list of awesome network analysis resources.

awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

awesome-python-cn

Python资源大全中文版，包括：Web框架、网络爬虫、模板引擎、数据库、数据可视化、图片处理等，由伯乐在线持续更新。

chinese-ai-developer

👩🏿‍💻👨🏾‍💻👩🏼‍💻👨🏽‍💻👩🏻‍💻** AI 开发者项目列表 -- 分享大家都在做什么

course-v3

The 3rd edition of course.fast.ai

d2l-zh

《动手学深度学习》，英文版即伯克利深度学习（STAT 157，2019春）教材。面向中文读者、能运行、可讨论。

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

deep-learning-with-pytorch-tutorials

深度学习与PyTorch入门实战视频教程

deeplearningbook-chinese

Deep Learning Book Chinese Translation

enar

enaR = Ecological Network Analysis in R

eu-ida

Index decomposition analysis of carbon emissions from electricity generation in the European Union

extracting_matrices_from_wiod_for_mrio

Converts deflated WIOTs in a long format into a wide table format and extracts matrices Z, Y and V for 2000-2014. Useful for conducting MRIO/SDA analysis.

fabio-spa

Structural Path Analysis in hybrid FABIO model

fastai-ml-dl-notes-zh

:book: [译] fast.ai 机器学习和深度学习中文笔记

hands-on-machine-learning

A series of Jupyter notebooks with Chinese comment that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

hello-world

igraph

Library for the analysis of networks

io-footprinting-spa

Input-output analysis calculations for footprinting

kaggle

Kaggle 项目实战（教程） = 文档 + 代码 + 视频（欢迎参与）

machine-learning-6-practical-real-world-app

This repo contains the code from the course Machine Learning Practical 6 Real-World Applications

machine-learning-combined-cycle-power-plant-data-set

The dataset contains data points collected from a Combined Cycle Power Plant over 6 years (2006-2011), when the power plant was set to work with full load. Features consist of hourly average ambient variables Temperature (T), Ambient Pressure (AP), Relative Humidity (RH) and Exhaust Vacuum (V) to predict the net hourly electrical energy output (EP) of the plant.

mrio-sda-using-pymrio

Performs an SDA analysis in an EE-MRIO framework using WIOD world input output tables and CO2 emissions data (2000-2014). Includes code on extraction of data.

multi-objective-attack-power-grid

The relevant codes of our work "Revealing Structural and Functional Vulnerability of Power Grids to Cascading Failures".

networkx

Official NetworkX source code repository.

nndl.github.io

《神经网络与深度学习》 Neural Network and Deep Learning

play-with-machine-learning-algorithms

Code of my MOOC Course <Play with Machine Learning Algorithms>. Updated contents and practices are also included. 我在慕课网上的课程《Python3 入门机器学习》示例代码。课程的更多更新内容及辅助练习也将逐步添加进这个代码仓。