Beginning Mathematica and Wolfram for Data Science: Applications in Data Analysis, Machine Learning, and Neural Networks

© Jalil Villalobos Alva 2021

J. Villalobos AlvaBeginning Mathematica and Wolfram for Data Sciencehttps://doi.org/10.1007/978-1-4842-6594-9_8

8. Machine Learning with the Wolfram Language

Jalil Villalobos Alva¹  

(1)

Mexico City, Mexico

 

The section will consist of the introduction of the gradient descent algorithm as an optimization method for linear regression; the corresponding computations will be shown as well as the concept of the learning curve of the model. Later, we will see how to use the specialized functions of the Wolfram Language for machine learning such as Predict, Classify and ClusterClassify, in the case of linear regression, for logistic regression and for cluster search. Adding to this, the different objects and results that these ...