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.
Reinforcement learning relies on an agent learning to determine accurate solutions from its own actions and the results produced in a contained environment.
Machine learning algorithms fuel machine learning models. They consist of three parts: a decision process, an error function and a model optimization process.
Supervised learning is an approach to machine learning that uses labeled data sets to train algorithms in order to properly classify data and predict outcomes.
Python is a popular programming language to use in machine learning because it offers developers exceptional versatility and power while integrating with other software.
