A machine learning task where the model predicts a continuous numerical value.
A machine learning task where the model predicts a continuous numerical value. Predicting house prices, stock returns, or temperature are regression problems. Linear regression is the simplest form; neural networks can handle much more complex regression tasks with non-linear relationships.
The most common machine learning approach: training a model on labeled data where each example comes with the correct answer.
A machine learning task where the model assigns input data to predefined categories.
A mathematical function that measures how far the model's predictions are from the correct answers.
A mathematical function applied to a neuron's output that introduces non-linearity into the network.
An optimization algorithm that combines the best parts of two other methods — AdaGrad and RMSProp.
Artificial General Intelligence.
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