Practical Implementation of Machine Learning Techniques and Data Analytics Using R

In this digital era all E-commerce activities are based on the modern recommendation systems where a company wants to analyse the buying pattern of its customers to optimize their sales strategies which mainly includes focusing more on valuable customers which is based on the amount of purchase made by customer rather than the traditional way of recommending a product. In the modern recommendation systems different parameters are synthesized for designing efficient recommendation systems. In this paper the data of 325 customers who have made certain purchases from a website having naive parameters like age, job type, education, metro city, signed in with company since and purchase history are considered. The E-commerce business model’s profit making is primarily dependent on choice-based recommendation systems. Hence in this paper a predictive model using machine learning-based linear regression algorithm is used. The study is done using a popular statistical tool named R programming. In this study the R tool is explored and represented with utility for recommendation system designing and finding insights from data by showing various plots. The results are formulated and presented in a formal and structured way using the R tool. During this study it has been observed that the R tool has potential to be one of the leading tools for research and business analytics.