Description

Qeexo AutoML is a fully-automated, end-to-end machine learning platform that builds lightweight machine learning solutions (tinyML) running locally on constrained environments at the Edge. It augments the user experience and applicability of products like the RA Family of MCUs, adding intelligence with AI.

Key Features

  • Supports Arm® Cortex™- M0 to M4 class MCUs like Renesas Synergy S5D9 and Renesas RA6M3
  • Enables a wide range of machine learning methods, including: GBM, XGBoost, Random Forest, Logistic Regression, CNN, RNN, ANN, Local Outlier Factor, and Isolation Forest
  • Libraries generated from Qeexo AutoML are optimized for constrained Endpoint device architectures: low latency, low power consumption, small footprint
  • Automates tedious and repetitive machine learning processes – saves time/cost to production and eliminates room for error
  • Zero coding necessary; machine learning expertise not required

Block Diagram

Qeexo AutoML Diagram

Target Markets and Applications

  • Wearables
  • Industrial
  • Mobile
  • IoT
  • Automotive
  • Smart Home/Appliances

TitleTypeLast Updated DateSize
Qeexo AutoML for Embedded Devices
Qeexo AutoML for Embedded Devices for the Renesas RA Partner Ecosystem
PDF 07 May 2020 342 KB

Disclaimer: THIS MATERIAL IS PROVIDED “AS-IS” FOR EVALUATION PURPOSES ONLY. RENESAS ELECTRONICS CORPORATION AND ITS SUBSIDIARIES (collectively, “Renesas”) DISCLAIM ALL WARRANTIES, INCLUDING WITHOUT LIMITATION, FITNESS FOR A PARTICULAR PURPOSE AND MERCHANTABILITY. Renesas provides evaluation platforms and design proposals to help our customers to develop products. However, factors beyond Renesas' control, including without limitation, component variations, temperature changes and PCB layout, could significantly affect the product performance. It is the user’s responsibility to verify the actual circuit performance.