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algorithms

Bug-tracking for Jeff's algorithms book, notes, etc.

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。

baiduhuiyan_qianxi

百度慧眼 迁徙数据 Crawling

big-data-spring2017

Materials for the Big Data, Visualization, and Society course at MIT DUSP - Spring 2017

data-visualization

Misc data visualization projects, examples, and demos: mostly Python (pandas + matplotlib) and JavaScript (leaflet).

deeplearning

深度学习相关教程

dviz-course

Data visualization course material

geneticalgorithmswithpython

source code from the book Genetic Algorithms with Python by Clinton Sheppard

how_to_make_data_amazing

This is the code for the "How to Make Data Amazing - Intro to Deep Learning #5" by Siraj Raval on Youtube

introduction-to-spatial-temporal-statistics

Introduction to Spatial-Temporal Statistics

iptv

Collection of 5000+ publicly available IPTV channels from all over the world

jour491-data-visualization

Course materials for a data visualization course taught at the University of Nebraska-Lincoln's College of Journalism and Mass Communications

learning-python-for-data-analysis-and-visualization

IPython notebook containing tutorials about python and data siance stack

nyc-taxi-data

Import public NYC taxi and Uber trip data into PostgreSQL / PostGIS database, analyze with R

oreilly-matplotlib-course

Jupyter notebooks from my O'Reilly Media course "Matplolib for Developers: Data Visualization and Analysis with Python"

python-practical-application-on-climate-variability-studies

This tutorial is a companion volume of Matlab versionm but add more. Main objective is the transference of know-how in practical applications and management of statistical tools commonly used to explore meteorological time series, focusing on applications to study issues related with the climate variability and climate change. This tutorial starts with some basic statistic for time series analysis as estimation of means, anomalies, standard deviation, correlations, arriving the estimation of particular climate indexes (Niño 3), detrending single time series and decomposition of time series, filtering, interpolation of climate variables on regular or irregular grids, leading modes of climate variability (EOF or HHT), signal processing in the climate system (spectral and wavelet analysis). In addition, this tutorial also deals with different data formats such as CSV, NetCDF, Binary, and matlab'mat, etc. It is assumed that you have basic knowledge and understanding of statistics and Python.

pywgs84togcj02

Python WGS84 To GCJ02 aka 火星坐标转换

simpleremote

Remote Administration Tools

urban-data-science

Course materials, Jupyter notebooks, tutorials, guides, and demos for a Python-based urban data science course.

yangtze-river-economic-belt-analysis

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