Optimizing Deep Learning: A Comprehensive Guide to Batch Normalization

Optimizing Deep Learning: A Comprehensive Guide to Batch Normalization

ByKishore

Batch Normalization (BN) is a technique used in deep learning to improve the training of deep neural networks by reducing the internal covariate shift problem. This problem occurs when the distribution of the inputs to each layer of the network changes during training, making it difficult to train the network effectively. BN addresses this issue…

Effective Feature Selection Techniques for Improved Model Performance

Effective Feature Selection Techniques for Improved Model Performance

ByKishore

Introduction Feature selection is a crucial step in building machine learning models, as irrelevant or redundant features can hinder model performance. In this blog post, we will explore two essential feature selection methods and apply them to a real-world dataset: eliminating low variance features and recursive feature elimination using cross-validation. Eliminating Low Variance Features: One…