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BLOG Model Performance Evaluation in Qeexo AutoML
Introduction Qeexo AutoML provides feedback on trained models through tables and charts. These visualizations can be useful in determining how models trained in Qeexo AutoML should perform in live classification and can help form suggestions for how...
Dr. Geoffrey Newman, Dr. Leslie Schradin III, Tina Shyuan 10 September 2021 -
BLOG Cross-Platform Swift at Scale
The dream of every developer is to be able to write code once and deploy everywhere. This allows for smaller teams to deploy more reliable products to a wider variety of users. Unfortunately, due to the numerous different operating systems with...
Alex Taffe 14 July 2021 -
BLOG Tree Model Quantization for Embedded Machine Learning Applications
This blog post is a companion to my talk at tinyML Summit 2021. The talk and this blog overlap in some content areas, but each also has unique content that complements the other. Please check out the video if you are interested. Why Quantization?...
Dr. Leslie J. Schradin, III 28 May 2021 -
BLOG Introducing Qeexo Model Converter
Our latest API service for fitting your existing ML models onto an embedded target as small as a Cortex-M0+! Qeexo AutoML offers end-to-end machine learning with no...
Gilbert Tsang, Director of Product Management 29 April 2021 -
BLOG Live Classification Analysis
Qeexo AutoML enables machine learning application developers to do analysis of different performance met- rics for their use-cases and equip them to make decisions regarding ML models like tweaking some training parameters, adding more data etc....
Sidharth Gulati, Dr. Rajen Bhatt 03 November 2020 -
BLOG Sensitivity Analysis with Qeexo AutoML
For machine learning models, Sensitivity parameter reflects on how sensitive the model is for classes under consideration. Sensitivity Analysis is generally performed before deployment of ML models in the real world application. The primary...
Qifan He, Dr. Rajen Bhatt 29 October 2020