Implementing a Fritz AI Machine Learning Model in an iOS app

Implementing a Fritz AI Machine Learning Model in an iOS app

In this article, we’ll walk you through the process of creating an image labeling ML model that can identify different car logos, and then integrating the model into an iOS app.

Fritz AI allows developers to use mobile-optimized machine learning (ML) algorithms to create custom ML models (without code) for use in their apps.

In this article, we’ll walk you through the process of creating an image labeling ML model that can identify different car logos, and then integrating the model into an iOS app.

How to Train an ML Model using Fritz AI Studio

The Fritz AI build system begins with creating an account and signing up for a plan that works best for you.

Currently, Fritz AI offers a “Sandbox” option, which is free to the user until they require more than five training hours (monthly global limit). First, make an account by navigating to the Fritz AI website, clicking “sign up”, and selecting “Sandbox” for the free option.

Note: Ensure you’ve selected Fritz AI Studio for your Sandbox account. You can always change this later, but to get started quickly, ensure you’ve selected the correct option.

Training a machine learning model with a pre-programmed platform like Fritz AI makes machine learning easy for people who are just starting out with machine learning or don’t know how to code. Alternatively, it’s a good way for companies to allow multiple people to work on ML models if they want uniform ML models that are all created in the same way. This platform also ensures accuracy and limits the margin of error for creating a custom ML model specifically for mobile deployment.

Step 1: Create a Project in Fritz AI Studio

We’re going to select the “custom” option and train our model to identify different vehicle manufacturer logos. Given that pre-trained models will most likely not exist for niche datasets (such as this one), we’ll walk you through the steps of labeling your images to train a custom model.

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