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Building a regression model
Cellular modem for Linux devices
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Platform
Application development
Blueprints
Workbench
Web IDE
Command line interface (CLI)
Edge ML
Edge infrastructure
Bare metal runtime
Particle on Linux
OTA software updates
Drivers and libraries
Device protection
Cloud infrastructure
Event bus
Ledger
Logic
Location Fusion
REST API
Integrations
Network and connectivity
"It just works" connectivity
Particle.publish()
Encryption
EtherSIM
EtherSIM+
Multi-radio transport
Management and oversight
Console
Software releases
Vitals
Security and compliance
Configuration
Insights
Supported devices
Single-board computers
Tachyon
M-HAT
M1 Enclosure
System-on-Modules (SoMs)
M-SoM
B-SoM
P2
Shop all SoMs
Accessories
Development boards
Muon
Boron
Photon 2
Shop all dev boards
Accessories
Gateways
Monitor One
Tracker One
Shop all gateways
Accessories
Solutions
By use case
Asset tracking
Preventative maintenance
Equipment monitoring
By industry
Emissions monitoring
Smart energy
HVAC
Light electric vehicles
By service
Professional services
Design & engineering services
Partners
Developers
Documentation
Hardware overview
Setup
Device OS
Cloud
Console
Ledger & Logic
Tutorials
Blink an LED
Read a photo sensor
Make a motion detector
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Blog
Introducing the M-series
From insights to action
Satellite IoT
Rethinking field connectivity
Connect IoT devices to Tulip
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Weather dashboard with LVGL, cloud secrets, and Ledger
Particle for Linux with the Magic Mirror project
Reliably classify hand gestures using proximity and light data.
Build energy-efficient applications using Particle’s Gen 4 devices.
Use an LTE-enabled module to remotely gather training data for an AI model.
Pricing
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