Deploying Machine Learning Models
Wei-Meng Lee · 2019
The main goal of machine learning is to create a model that the coders can use for making predictions. This chapter shows how to deploy the machine learning model using the Flask micro-framework. It also shows how the coders can view the correlations between the various features and then only use those most useful features for training their model. The chapter aims to evaluate several machine learning algorithms and choose the best performing one so that the coders can choose the correct algorithm for their specific dataset. Logistic regression, K-Nearest Neighbors, support vector machines—Linear and RBF kernels are considered as best performance algorithm.