Tagged | GeoData
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The GIS Journey at Blinkit (formerly Grofers)
(lambda.grofers.com) -
Serve Map Clusters 50x Faster Using Smarter Caching
(www.toptal.com) -
MetNet-2: Deep Learning for 12-Hour Precipitation Forecasting
(ai.googleblog.com) -
How and why to build your own gradient boosted-tree package
(eng.lyft.com) -
Efficient Point in Polygon Joins via PySpark and BNG Geospatial Indexing
(databricks.com) -
Mapping Africa’s Buildings with Satellite Imagery
(ai.googleblog.com) -
‘Orders Near You’ and User-Facing Analytics on Real-Time Geospatial Data
(eng.uber.com) -
Using Client-Side Map Data to Improve Real-Time Positioning
(eng.lyft.com) -
Identifying Financial Fraud With Geospatial Clustering
(databricks.com) -
Labeling Satellite Imagery for Machine Learning
(www.azavea.com) -
A Neural Weather Model for Eight-Hour Precipitation Forecasting
(ai.googleblog.com) -
Understanding Micro-Mobility Patterns using Geospatial Data
(towardsdatascience.com) -
Three Ways to Get Into the “Mind” of a Supervised Machine Learning Model
(www.azavea.com) -
Article: Predicting Time to Cook, Arrive, and Deliver in Uber Eats
(www.infoq.com) -
New Insights into Human Mobility with Privacy Preserving Aggregation
(ai.googleblog.com) -
Improving Pickups with Better Location Accuracy
(eng.uber.com) -
Identifying gaps in OpenStreetMap coverage through machine learning
(towardsdatascience.com) -
MaRS: How Facebook keeps maps current and accurate
(engineering.fb.com) -
An Inside Look at Flood Forecasting
(ai.googleblog.com) -
How Map Matching Failures can be used for Map Making
(eng.lyft.com) -
Mapping roads through deep learning and weakly supervised training
(ai.facebook.com)#machine-learning #image-processing #GeoData #research #maps
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Using Noisy Labels to Train Deep Learning Models on Satellite Imagery
(www.azavea.com) -
Mapping roads through deep learning and weakly supervised training
(ai.facebook.com) -
The Scooters Are Coming: let’s require data this time
(www.azavea.com) -
Visualizing City Cores with H3, Uber’s Open Source Geospatial Indexing System
(eng.uber.com) -
Predicting Bus Delays with Machine Learning
(ai.googleblog.com) -
Power On: Accelerating Uber’s Self-Driving Vehicle Development with Data
(eng.uber.com) -
Visualizing Traffic Safety with Uber Movement Data and Kepler.gl
(eng.uber.com) -
Analyzing Spatial Patterns in Life Expectancy with Python
(www.azavea.com) -
Improving Uber’s Mapping Accuracy with CatchME
(eng.uber.com) -
Guiding you Door-to-Door via our Super App!
(engineering.grab.com) -
Solving A Data Science Challenge - The Visual Way
(towardsdatascience.com) -
Using Global Localization to Improve Navigation
(ai.googleblog.com) -
A new predictive model for more accurate electrical grid mapping
(research.fb.com) -
How Uber Beacon Helps Improve Safety for Riders and Drivers
(eng.uber.com) -
Technical workflow: Building transportation scenarios for accessibility analysis
(towardsdatascience.com) -
Exploring & Machine Learning for Airbnb Listings in Toronto
(towardsdatascience.com) -
Visualizing Air Pollution with Folium Maps
(towardsdatascience.com) -
Using Calibration to Translate Video Data to the Real World
(devblogs.nvidia.com) -
How to solve the last mile logistics conundrum?
(towardsdatascience.com) -
Raster Vision: A New Open Source Framework for Deep Learning on Satellite and Aerial Imagery
(www.azavea.com) -
Uber Expands Advanced Visualization Ecosystem with Mapbox Integration
(eng.uber.com) -
Digitizing Maps Using Remote Sensing Techniques in ArcMap and R
(www.azavea.com) -
Creating Leaflet Tiles from Open Data using PostGIS and QGIS
(www.azavea.com) -
Coral Cities: An Ito Design Lab Concept
(towardsdatascience.com) -
A Cartographic Exploration of Housing in Amsterdam
(towardsdatascience.com) -
New data tools for relief organizations: network coverage, power, and displacement
(research.fb.com) -
Generating Pyramided Tiles from a GeoTIFF using GeoTrellis
(www.azavea.com) -
Enhancing the Quality of Uber’s Maps with Metrics Computation
(eng.uber.com) -
How to use Machine Learning and Quilt to Identify Buildings in Satellite Images
(blog.insightdatascience.com) -
H3: Uber’s Hexagonal Hierarchical Spatial Index
(eng.uber.com) -
Introducing Commute Time for Jobs
(engineering.linkedin.com) -
From Beautiful Maps to Actionable Insights: Introducing kepler.gl, Uber’s Open Source Geospatial Toolbox
(eng.uber.com) -
Growing the Data Visualization Community with deck.gl v5
(eng.uber.com) -
Rethinking GPS: Engineering Next-Gen Location at Uber
(eng.uber.com) -
The Comprehensive Beginner’s Guide to JavaScript Geolocation Tracking
(hackernoon.com) -
You Are (Probably) Here: Better Map Pins with DBSCAN & Random Forests
(engineering.foursquare.com) -
Analyzing Climate Patterns with Self-Organizing Maps (SOMs)
(towardsdatascience.com) -
Geo-blocking media content on Pinterest
(medium.com) -
Predicting Land Use in the Amazon using Deep Learning
(www.azavea.com) -
Geo-Spatial Search on Mobile: Quick but Not Dirty
(blog.algolia.com) -
Serving Tiles with GeoTrellis, Lambda, and API Gateway
(www.azavea.com) -
Comparison of 4 Point Data Aggregation Methods for Geospatial Analysis
(www.azavea.com) -
How to Build A Boba Tea Shop Finder with Python, Google Maps and GeoJSON
(twilioinc.wpengine.com) -
Introducing GeoPySpark, a Python Binding of GeoTrellis
(www.azavea.com) -
Pre-Processing GeoTIFF files and training DeepMask/SharpMask model
(software.intel.com) -
Getting Started on Geospatial Analysis with Python, GeoJSON and GeoPandas
(twilioinc.wpengine.com) -
Periscope Data | Geographic Analysis in SQL: Measuring Polygon Area from Latitude and Longitude
(webflow-blog.periscopedata.com)