Qeexo AutoML supports three one-class classification algorithms widely used for anomaly/outlier detection; Isolation Forest, Local Outlier Factor, and One-class Support Vector Machine. These algorithms build models by learning from only one class of data.

Inference settings contain two important parameters; Instance length and Classification interval. In this blog, we will explain the Classification Interval and in conjunction with raw sensor signals, ODR, Instance length, latency, and performance of the model on the embedded target.

Qeexo AutoML enables machine learning application developers to customize inference settings based [...]

First company to build an automated ML platform for the Arm Cortex-M0 [...]

Introduction Sound Recognition is a technology based on traditional pattern recognition theories [...]

Qeexo, the “tinyML” specialist, said its AutoML platform now supports the smallest Cortex processors from Arm Ltd., making it the first vendor to automate machine learning on the Arm processor used for edge computing in sensors and microcontrollers.

The team here at insideBIGDATA is deeply entrenched in following the big data ecosystem of companies from around the globe. We’re in close contact with most of the firms making waves in the technology areas of big data, data science, machine learning, AI and deep learning. Our in-box is filled each day with new announcements, commentaries, and insights about what’s driving the success of our industry so we’re in a unique position to publish our quarterly IMPACT 50 List of the most important movers and shakers in our industry. These companies have proven their relevance by the way they’re impacting the enterprise through leading edge products and services. We’re happy to publish this evolving list of the industry’s most impactful companies!

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 objective of the Sensitivity Analysis is to make ML model lean more towards certain class(es) than the other(s).

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. based on those real-time test data metrics. In this article, we will discuss in detail regarding live classification analysis module.

Since mid-September, 10 teams of LeTourneau University engineering students have been working on projects involving artificial intelligence to enter into a contest. Winners of that contest were announced Friday in the lobby of the Glaske Engineering Center after demonstrations from students.

So-called smart devices like Amazon Echo and Google Nest made early headway into our homes. But will devices as small as a vibration sensor soon outsmart an Echo? Here's a look under the hood of "TinyML."

Click HERE to view the video Full URL to video source: https://www.kltv.com/video/2020/11/06/machine-learning-contest/

2020 has been year for the ages, with so many domestic and global challenges. But the big data industry has significant inertia moving into 2021.

The team here at insideBIGDATA is deeply entrenched in following the big data ecosystem of companies from around the globe. We’re in close contact with most of the firms making waves in the technology areas of big data, data science, machine learning, AI and deep learning. Our in-box is filled each day with new announcements, commentaries, and insights about what’s driving the success of our industry so we’re in a unique position to publish our quarterly IMPACT 50 List of the most important movers and shakers in our industry.

IoT enables continuous monitoring of environments and machines using tiny sensors. Advances [...]

Company also debuts the Qeexo Model Converter to optimize customers’ existing machine [...]

Intelligent decision-making has moved to the edge with machine learning, though deployment could be complicated. Qeexo and STMicroelectronics are looking to change that.

This blog post is a companion to my talk at tinyML Summit [...]