AI Model Training Primer: Train Your Own Model from Scratch

🎓 Model Training Primer — Build Your Own Model

🔄 Training Lifecycle

1. Data collection: get enough training data (images / text)
2. Preprocessing: clean, label, format
3. Model design: choose network structure and parameters
4. Training: feed data, tune params, watch metrics
5. Evaluation: test on an independent set
6. Deployment: integrate into the real application

🎯 Practice: Fruit Classification Model

Train to recognize apple / banana / orange / grape:

Step 1 — Data Prep

• At least 100 photos per fruit (different angles / light / background)
• Organize by folder: datasets/apple/, datasets/banana/…

Step 2 — Transfer Learning

• Fine-tune a pretrained model (MobileNetV2)
• Train only the last few layers, saving time and compute

Step 3 — BitCreator AutoML

The built-in AutoML module simplifies the flow — upload folders, choose a model, one-click train and export, no code needed!