Project Base Prediction Using Machine Learning and Deep Learning

Abstract

The goal of this work is to undertake a survey of the literature on machine learning trends and techniques for predictive analysis. We conducted a combination of studies from three scientific programmes to achieve this. Following that, we thought about the selection criteria we would use to only look at publications from the last five years. This study's goal is to let researchers, businesses, or anybody else wishing to perform Data cleansing, data analysis, statistical analysis, exploratory analysis, predictive analysis, and correctness of the project are all necessary for them to be able to select the most effective ML technique (s). With this study, the project's most popular techniques were emphasised and made simple to use. We were also able to analyse the project's interquartile range and outlier range.