TinyML AutoML Tutorial: Building Production-ready Models with Imagimob AI

Dive into a comprehensive tutorial on building production-ready models using Imagimob AI for tinyML applications. Explore the Imagimob AI development platform, designed to streamline the creation of Artificial Neural Network (ANN) models for time-series data on resource-constrained devices. Learn about the platform's low-code approach while gaining access to powerful tools for sensor connection, data visualization, preprocessing, and model integration. Follow along as the tutorial covers key concepts including data interpretation, management, and properties, as well as model training, evaluation, and real-world examples. Gain insights into handling slow dynamics, noise in ML models, recurrent networks, and segmentation techniques. Discover whether Imagimob Studio is available on-premise or in the cloud, and understand how this platform can accelerate your tinyML development process.

Introduction
Overview
Conceptualization
Data Visualization
Data Interpretation
Data Management
Data Properties
Preprocessing
Model Wizard
Training Models
Model Evaluation
Real World Example
Looking at the Models
Back to the Slides
Summary
Slow Dynamics
Can ML Model Handle Noise
Do you have support for recurrent
Can you elaborate on segmentation
Is imagimob Studio onpremise or cloud
Conclusion