AI / ML

Improving Dataset Creation for Machine Learning

Written in collaboration with Andreas Putz, Computer Scientist at MistyWest. Introduction Over the past decade, one of the hottest areas of innovation has been to apply machine learning to real-world applications. Google and Amazon are now using machine learning models to transcribe speech to text, interpret language, and analyze images and videos. However, to achieve …

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How To Train Your Wearable Device

Introduction Leveraging ML Components to Unlock Powerful Low Power Applications Motion Sensors, or Inertial Measurement Units (IMUs), in wearable connected devices have long been able to internally detect limited human interactions (such as tapping) and in some cases, very specific orientations (such as a wrist tilt) while using low power consumption. Detecting complex motions, like …

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Robotic Steve II: Eyes

Written by Ryan Walker, former MistyWest employee. As you learned in the first part of our RoboSteve series, we are building a Machine Learning and Machine Vision platform inspired by our office dog Steve. There’s only one thing biological Steve loves more than food, and that’s playing with his girlfriend Miso. In order to emulate …

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Robotic Steve I: Origins

A few weeks back, a handful of brave Westies began a quest to build a robot dog. When this concept was pitched, it was widely regarded as some animatronic dog covered in servos that would walk around – in reality, it’s a Machine Learning and Machine Vision platform. The goals of the project are to …

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Breaking Down Handwriting With ML

Written by Justin Girard, former Westie   Classification of Handwritten Numbers When trying to get a grasp on how machine learning (ML) works, it is often useful to experiment with existing ML problems. One popular starting point is the MNIST database (Modified National Institute of Standards and Technology), a collection of image scans of handwritten …

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