7 Must-Know Algorithms in Machine Learning

An ML model is a collection of rules and preferences applied to a dataset, which enables computers to make predictions. Learning includes collecting data, cleaning it, and training the model using more powerful algorithms and/or new datasets. Once trained, your computer can make predictions with high accuracy over many cases. While there are techniques like gradient descent, transfer learning, batch normalisation, etc, for enhancing models, there are various algorithms that are useful for solving different types of problems and training a model. This article covers algorithms for training machine learning models, including neural networks, bayesian inference, and probabilistic inference.