What is Hyperparameters?
Settings you choose before training an AI model that control how the training process works.
Why It Matters
The right hyperparameters can mean the difference between a model that works well and one that does not.
Real-World Example
Choosing the learning rate, batch size, and number of training epochs before starting model training.
“Understanding terms like Hyperparameters matters because it helps you have better conversations with developers and make smarter decisions about your software. You do not need to be technical. You just need to know enough to ask the right questions.”
Related Terms
Learning Rate
A number that controls how much an AI model adjusts its knowledge from each batch of training data.
Batch Size
The number of training examples an AI model processes at once before updating its knowledge.
Epochs
The number of times an AI model goes through the entire training dataset during training.
Overfitting
When an AI model memorises its training data too closely and performs poorly on new, unseen data.
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Related Terms
Overfitting
When an AI model memorises its training data too closely and performs poorly on new, unseen data.
Batch Size
The number of training examples an AI model processes at once before updating its knowledge.
Learning Rate
A number that controls how much an AI model adjusts its knowledge from each batch of training data.
Epochs
The number of times an AI model goes through the entire training dataset during training.
Large Language Model (LLM)
An AI system trained on massive amounts of text that can understand and generate human language.
Transformer
A type of AI architecture that processes text by paying attention to relationships between all words at once, rather...