A support vector machine is a linear machine learning model for classification and regression problems. Learn how it works and how to implement it in Python.
Data leakage occurs when unexpected additional information infiltrates a training algorithm. Our expert explains what you need to look out for and how to solve this problem.
Model deployment is the process of integrating a machine learning model into a production environment where it can take in an input and return an output.
Machine learning algorithms fuel machine learning models. They consist of three parts: a decision process, an error function and a model optimization process.
Feature importance involves calculating a score for all input features in a machine learning model to determine which ones are the most important. Here’s how to do it.
Non-maximum suppression (NMS) is a post-processing technique that is used in object detection tasks to eliminate duplicate detections and select bounding boxes.
A plethora of cost-effective machine learning solutions put the power of these tools at your fingertips. Our expert shares some ways small business owners can take advantage of them.
