The Three-Step Machine Learning Process

1
Data Collection
Gathering relevant, representative datasets with quality considerations for completeness, accuracy, and relevance.
📊
📈
🗂️
💾
📚 Like gathering study materials for a comprehensive exam
2
Training
Algorithm learns patterns from training data through iterative improvement processes.
🧠
⚙️
📝
🔄
📖 Like studying for a test using practice problems
3
Prediction
Making predictions on new, unseen data with performance evaluation.
🎯
🔮
📋
📝 Applying what you learned to solve new problems
Process Flow in Action
1

Input Data

Raw datasets, features, labels

2

Learning Algorithm

Pattern recognition, weight adjustment

3

Trained Model

Ready to make predictions

4

New Data

Unseen examples for testing

5

Predictions

Classifications, recommendations