Training

Definition

The computationally intensive process where a machine learning algorithm is fed data and iteratively adjusts its internal mathematical parameters (weights and biases) to minimize errors and improve its accuracy.

Explain Like I'm New

Going to the gym for your brain. The AI takes a guess, sees it was wrong, adjusts its math slightly, and takes another guess. It repeats this millions of times until it gets very good at guessing.

Real World Example

Training ChatGPT took months of processing time on thousands of Nvidia GPUs running 24/7. It read text, guessed the next word, checked if it was right, and adjusted its internal brain slightly.

Common Use Cases

•Model creation
•Compute optimization

Interview Questions

basic

Which requires significantly more computing power: Training a model, or using a model to make a prediction?

intermediate

What is 'Overfitting' during the training process?

Flash Cards

Question

More compute power?

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Answer

Training! Training requires supercomputers and months of time. Using the model (Inference) can often be done on a standard laptop or smartphone in seconds.

Question

What is Overfitting?

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Answer

When a model memorizes the training data too perfectly. It's like a student memorizing the exact answers to a practice test but failing to understand the underlying concepts. When the student takes the real test (unseen data), they fail completely.