When solving problems with AI, the first step is selecting the right model for the task at hand. This means understanding the type of problem you’re trying to solve and matching it with a model that is capable of learning from data and providing a solution. The model you choose should be suited to the kind of data you have and the results you want to achieve.

Image Recognition
Task: Recognising different types of objects in images (e.g., distinguishing between a cat and a dog in photos).

Voice Recognition
Task: Identifying different voices or understanding spoken commands (e.g., recognising a specific person’s voice).

Pose Recognition
Task: Detecting specific body poses or movements (e.g., recognising a person performing yoga poses).

Predicting Data
Task: Predicting missing values or making forecasts based on past data (e.g., predicting future sales from past trends).

Here are some simple AI models you can use for these tasks:

Teachable Machine

• Use for: Image recognition, sound classification, and pose detection.
• Why use it?: It’s beginner-friendly and allows you to easily train models using your own data, such as images or audio files.

Machine Learning for Kids

• Use for: Image recognition, voice recognition, and simple predictive models.
• Why use it?: It provides a user-friendly interface for training AI models using different types of data, such as images, sounds, and text.

By selecting the right model for your problem, you can start the process of training your AI and applying it to real-world situations.