On a mission to provide Pune, India with a free IOT data network! We are building a free (as in beer), open network (free as in speech), based on an open-source stack, owned by the …
The Nicla Sense ME is a tiny, low-power tool that sets a new standard for intelligent sensing solutions. With the simplicity of integration and scalability of the Arduino ecosystem, the board combines four state-of-the-art sensors from Bosch Sensortec: BHI260AP motion sensor system with integrated AI BMM150 magnetomete
hello ,I'm trying to implement a KNN (K-Nearest Neighbors) model for classification in MATLAB (Similar Image Finder project). do you know how to determine the optimal number of neighbors (k) for the datase
Hi guys, I sent an invite to @anniekeerdekens for joining our group. Anniek is a good friend of mine. We studied together in the University of Leuven. Anniek did her PhD recently in machine learning and IoT devices for monitoring animal health and behavior (especially for horses).
Conventionally, the value of k is taken as sqrt(N) where N is the number of data points in your dataset. But a better approach is to take a random sample (5% of your main dataset) and use the trial and error method to find the optimal k value that works best for that particular sample.
Statistically, the optimal k value you find out in that sample should also be the optimal k value for your entire dataset.
I am interested to build a wifi clock and make it a viable product in this upcoming IoT market. Learning/Re-learning/Updating myself with an embedded course at www.binaryupdates.com
Dive into the world of visual binary analysis! Learn how to uncover hidden data and secrets within binary code. #BinaryAnalysis #DataEncryption #TechExplained #TechTips #CyberSecurityAwareness