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gptkbp:instanceOf
|
machine learning platform
|
|
gptkbp:developedBy
|
gptkb:Edge_Impulse
|
|
gptkbp:focusesOn
|
gptkb:TinyML
IoT applications
embedded machine learning
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Edge Impulse Studio
|
|
gptkbp:integratesWith
|
gptkb:Texas_Instruments
gptkb:NVIDIA_Jetson
gptkb:Google_Colab
gptkb:AWS
gptkb:Google_Cloud
gptkb:Arduino
gptkb:Raspberry_Pi
gptkb:Renesas
gptkb:STM32
gptkb:Silicon_Labs
gptkb:TensorFlow_Lite
gptkb:Azure
gptkb:Infineon
gptkb:Maxim_Integrated
gptkb:ON_Semiconductor
gptkb:Microchip
gptkb:Seeed_Studio
gptkb:Adafruit
gptkb:Espressif
gptkb:Sony_Spresense
Particle
Nordic Semiconductor devices
SparkFun
|
|
gptkbp:launched
|
2020
|
|
gptkbp:offers
|
gptkb:REST_API
gptkb:mobile_application
CLI tools
real-time data visualization
model optimization
drag-and-drop workflow
open source SDKs
on-device testing
|
|
gptkbp:provides
|
model deployment
model training
data acquisition tools
|
|
gptkbp:supports
|
gptkb:dictionary
regression
gesture recognition
anomaly detection
sensor data
time series data
object detection
audio data
image data
keyword spotting
custom ML models
|
|
gptkbp:usedFor
|
gptkb:consumer_electronics
agriculture
automotive
wearables
smart home
predictive maintenance
industrial IoT
healthcare devices
|
|
gptkbp:website
|
https://studio.edgeimpulse.com
|
|
gptkbp:bfsParent
|
gptkb:Edge_Impulse
|
|
gptkbp:bfsLayer
|
7
|