Gradient Descent

Reinforcement Learning

Reinforcement learning (RL) is a machine learning paradigm in which an agent learns to make decisions by taking actions in an environment and receiving rewards…

Overfitting

Overfitting occurs when a machine learning model learns the training data too closely, including its noise and idiosyncrasies, resulting in poor performance on…

Underfitting

Underfitting occurs when a machine learning model is too simple to capture the underlying patterns in the training data, resulting in poor performance on both…

Gradient Descent

Gradient descent is an optimization algorithm that iteratively adjusts a model's parameters in the direction that most reduces its error, or loss, in order to…

Backpropagation

Backpropagation is the algorithm used to train neural networks by efficiently computing how much each parameter contributed to the model's error, so those para…

Gradient Descent Cheat Sheet

The mechanics of gradient descent optimization, covering batch, stochastic, and mini-batch variants plus momentum and adaptive learning rate methods.