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jstraining

全栈工程师培训材料

klovien.github.io

本项目为Pages静态博客示范，对应的演示网站地址为 👉

laguna-landslide-svr

An attemp to map the landslide susceptibility of the province of Laguna by training SVR on an integrated weighted index generated using AHP and FR methods

landslide

Research project on building and evaluating deep learning models for landslides detection on satellite images

landslide-rainfall

Half-hourly IMERG rainfall during landslide event

landslide-susceptibility

Landslide susceptibility mapping by deep learning and slope unit

landslide-susceptibility-assessment-tool

landslide susceptibility assessment tool including 10 python script for ArcGIS software.

lazystudy

lightgbm-gbdt-lr

a python code of applying GBDT+LR for CTR prediction

lsat

Landslide Susceptibility Assesment Tool

lspmodelsforcageo

LSM_Model_Imbalanced

luct

We used the Google Earth Engine Code interface to create a classification of land use on the United States Virgin Islands (USVI). We used six classes: water, low density residential, high-density residential, forest/shrub, agriculture and barren. We included DEM, classification points, and landsat imagery bands to analyze the imagery. Our final product is at a 30 meter spatial scale.

lulc

to extract from classified image to csv for analyses

lulc-icimod

to make 30m LULC of Nepal for 2020

machine-learning-learning-notes

周志华《机器学习》又称西瓜书是一本较为全面的书籍，书中详细介绍了机器学习领域不同类型的算法(例如：监督学习、无监督学习、半监督学习、强化学习、集成降维、特征选择等)，记录了本人在学习过程中的理解思路与扩展知识点，希望对新人阅读西瓜书有所帮助！

mapdownload

地图下载器(正在开发中现在支持天地图下载)

marta-gans

Implementation of the paper "MARTA GANs: Unsupervised Representation Learning for Remote Sensing Image Classification".

mdb2shp

ml-and-dl

self-learning

ml_imblearn

类别不平衡学习，包括采样、代价敏感学习、决策输出补偿以及集成学习等内容

ms-remote-sens-2018

Materials for 2018 Tanintharyi land cover change analysis paper (De Alban et al. 2018. Remote Sensing).

ms_thesis

natural_disaster_pred

Using CNNs and Sentinel-2 satellite data to predict landslides

newcodeforlsp

nexgenmap

This repository have Google Earth Engine scripts that presents the results of LULC Classification of the article submited to Remote Sensing: Improving Land Use Land Cover Mapping with Machine Learning, PlanetScope imagery, and Google Earth Engine.

nsfc-latex

objectorientedlulc_gee

ol-cesium-test

基于Openlayers与Cesium的地图API集成测试系统

ol-vue-example

A showcase on how to integrate an OpenLayers map in a Vue.js codebase.

pumpkin-book

《机器学习》（西瓜书）公式推导解析，在线阅读地址：https://datawhalechina.github.io/pumpkin-book