Poverty Eradication Using ML
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About
Research Methods
Predicting poverty
Interpretable Poverty Mapping Using Social Media, Satellite Images and Geospatial Information
Predicting Economic Development Using Geolocated wikipedia articles
Generating Interpretable Poverty Maps using Object Detection in Satellite Images
Tile2Vec - Unsupervised representation learning
Efficient Poverty Mapping using Deep Reinforcement Learning
New directions (Ideas)
CDR Methods
Predicting poverty and wealth from Mobile phone metadata
Mobile phone Data
Resources for analyzing CDR
How to Measure poverty
Approches to Measuring Poverty
Data
Satellite Imagery
Survey Data
Multi Spectral Remote Sensing
Geograhic Data Processing
Geographic Data
Visualizing Buildings in a location along with its Area
Spatial Analysis using Geopandas
Coordinate Reference Systems (CRS)
Data Visualization using Folium
OpenStreetMap
Converting Data from Raster to Tabular (Geometry) format
Deep Learning Implementations
Satellite Images Classification
Telecom Churn Prediction
EDA on Telecom Churn Data
Telecom Churn Prediction
On this page
Resources for analyzing CDR
Python packages
Blogpost
Resources for analyzing CDR
Python packages
Bandicoot open source library by MIT
Cellyzer
Blogpost
CDR data analysis using Neo4j