An Approach of Machine Learning Algorithms Through Linear Algebra

Computing devices can utilize machine learning to forecast the future or make decisions without being specifically programmed. Machine learning is able to build smart algorithms and evaluate more data from facts. Machine learning is based on the study of vectors, matrices, planes, maps, and lines, all defined by way of the field of linear algebra. Linear algebra concepts are used to design algorithms in machine learning. It applies machine learning algorithms to work on large amount of amounts of data. In supervised and unsupervised machine learning, linear algebra concepts which include logistic regression, linear regression, decision trees, and component analysis are used.