TLDR:
Key points:
- AI training involves adjusting mathematical formulas to reduce error.
- Testing AI models on data not used for training is essential to assess accuracy.
AI training involves creating mathematical formulas to model relationships, such as sales revenue prediction based on product price and advertising costs. Initially, random values are assigned to model parameters, and adjustments are made based on errors in predictions. Testing the model on new data helps assess accuracy. Understanding the mathematical logic behind AI training is essential for developing effective models.