The project focuses on analyzing the factors that may have an impact on climate changes using ‘El NINO’ dataset that is downloaded from UCI Machine Learning Repository. Main focus of this project is to understand machine learning concepts and regression algorithms as well as focus on data analytics to understand/analyze the data and visualize using different libraries. Initial data analysis was done to understand the relationship between features and also answering few research questions that can help in getting insights of features and target variable.
The dataset contains oceanographic, and surface meteorological readings taken from a series of buoys positioned throughout the equatorial Pacific. The data was collected with the Tropical Atmosphere Ocean (TAO) array, which consists of nearly 70 moored buoys spanning the equatorial Pacific, measuring oceanographic and surface meteorological variables. The data consists of 178080 rows and 12 features taken from buoys as early as 1980-1990. All the readings were taken at the same time of the day from the buoys.