Batch Gradient Descent

Batch Gradient Descent is an optimization method used in machine learning to minimize errors in predictions. It works by calculating the average error across the entire dataset and then adjusting the model's parameters to reduce this error. Imagine trying to find the best route on a map—Batch Gradient Descent assesses the overall journey (the whole dataset) rather than just single turns (individual data points) to determine the most efficient path. This approach can lead to better and more stable results, but it may require more memory and processing time, especially with large datasets.