Basics of Machine Learning with Teachable Machine

Introduction

Machine learning (ML) is a cornerstone of modern artificial intelligence, enabling computers to learn from data rather than being explicitly programmed. Teachable Machine, a free online tool by Google, makes it easy for anyone, including students, to understand the basics of ML by building and training simple models.

What is Teachable Machine?

Teachable Machine is an intuitive platform that allows users to create ML models using images, audio, or poses as inputs. These models can classify data and perform tasks based on the input provided. No prior experience in ML or programming is required.

Step-by-Step Guide to Using Teachable Machine

Step 1: Access the Platform

• Visit Teachable Machine.
• Start a new project without needing to register an account.

Step 2: Choose a Project Type

• Image Projects: Ideal for recognizing visual patterns (e.g., gestures or objects).
• Audio Projects: Classify sounds or speech (not ideal for noisy classrooms).
• Pose Projects: Recognize body movements (requires space to move).

Step 3: Record Training Data

• Use a webcam to capture data for classification.
• Example: Train the model to distinguish between “Left” and “Right” gestures:
  • Record 30–50 images of your hand signaling “Left.”
  • Repeat the process for “Right.”
  • Add a “Nothing” class to handle default states.

Step 4: Train the Model

• Click “Train Model” to upload your data to the cloud.
• Wait a few seconds for the model to process the data and learn.

Step 5: Test the Model

• Use the webcam to test the model’s ability to classify gestures.
• Adjust the data if the model misclassifies or lacks confidence.

Expanding Your Model

• Enhance Usability: Add a “Nothing” class for neutral states to prevent misclassification.
• Increase Accuracy: Use diverse training data, including different lighting or angles.
• Export for Use: Export the trained model to integrate it into other applications.

Applications in Education

1. Interactive Learning: Use ML models in classroom games or experiments.
2. Creativity: Build projects that classify objects, emotions, or movements.
3. Problem-Solving: Encourage students to iterate on their models for improved performance.

Conclusion

Teachable Machine simplifies the complexities of machine learning, offering a hands-on way to explore AI. By creating and training models, students gain practical insights into how ML works and its real-world applications. Try Teachable Machine in your next lesson to inspire creativity and curiosity in the realm of artificial intelligence!