Support vector machine (SVM) is one of the simplest machine learning models. Understanding this is like learning basic to machine learning and progressing ahead.

Utilizing Machine Learning Models in Python. In this post lets explore how to share these models in applications.

A life cycle of a data science project is to typically start with a use case or idea, gather data from all available sources, analyze the data and perform feature engineering and build a statistical model that makes a good generalization on future data, and then deploy into production.

Different Regression models i.e. Linear Regression, Decision Tree Regression, Gradient Boosted Regression, and Random Forest Regression were used. The performance of those models using R² were compared. Based on these performance score, better performing model were suggested to predict house price.

The 7 Key Steps To Build Your Machine Learning Model. A Machine learning model is a mathematical depiction of real-word. You have to provide data training to build machine learning models.