Industrial Productivity Solutions Guide

This guide is a tutorial designed to assist users in utilizing the Edge Impulse platform for developing edge machine learning (ML) applications, specifically focusing on industrial predictive maintenance. It outlines the process of building an ML application, which includes data collection, cleaning, transformation, and digital signal processing (DSP) for feature engineering. The guide details the construction of ML models, including how to select, train, test, and tune them, as well as the deployment of the resulting inference library on various target devices. Additionally, it introduces the concept of an 'Impulse,' which is a key element in the Edge Impulse framework for managing ML workflows. The guide emphasizes the integration of collaboration tools and the importance of security and compliance, making it relevant for teams operating in the industrial productivity sector. Upcoming sections will further elaborate on the features and capabilities of Edge Impulse, providing insights into effective usage for machine health and productivity applications.