Euclidean distance measures the length of the shortest line between two points. It’s commonly used in machine learning algorithms. Learn how to calculate it in Python.
VGG16 is a convolutional neural net architecture that’s used for image recognition. It utilizes 16 layers with weights and is considered one of the best vision model architectures to date.
Density-based spatial clustering of applications with noise (DBSCAN) is a clustering algorithm used to define clusters in a data set and identify outliers. Here’s how it works.
Overfitting and underfitting are two problems that can occur when building a machine learning model and can lead to poor performance. Learn what causes them and how to fix it.
The rectified linear unit (ReLU) activation function introduces the property of nonlinearity to a deep learning model and solves the vanishing gradients issue. Here’s why it’s so popular.
Principal component analysis (PCA) in Python can be used to speed up model training or for data visualization. This tutorial covers both using scikit-learn.
