Day: May 1, 2020

Machine Learning and Data Science in Python using LightGBM with Ames Housing Price Dataset | Pandas

    Machine learning and data science are two areas of computer science that are used to analyze, understand, and make predictions about data. One of the most popular techniques for machine learning and data science is LightGBM (Light Gradient Boosting Machine), it’s a gradient boosting framework that uses tree-based learning algorithms. It’s designed to …

Machine Learning and Data Science in Python using XGBoost with Ames Housing Dataset | Pandas | MySQL

  Machine learning and data science are two areas of computer science that are used to analyze, understand, and make predictions about data. One of the most popular techniques for machine learning and data science is XGBoost (eXtreme Gradient Boosting). XGBoost is a type of ensemble method that combines multiple decision trees to make predictions …

Machine Learning and Data Science in Python using GBM with Ames Housing Dataset | Pandas | sklearn

      Machine learning and data science are two areas of computer science that are used to analyze, understand, and make predictions about data. One of the most popular techniques for machine learning and data science is Gradient Boosting Machine (GBM). GBM is a type of ensemble method that combines multiple decision trees to …

Time Series Analysis in R using Exponential Smoothing using BJ Sales Dataset | Data Science with R

  The BJ Sales dataset from UCI (University of California, Irvine) is a collection of 42 observations and 1 feature that are used to forecast the number of sales of a certain product in Beijing. Each observation represents a month, and the feature represents the number of sales for that month. The goal of this …