International Journal of Research and Innovation in Applied Science (IJRIAS) | Volume VII, Issue VII, July 2022 | ISSN 2454–6194
Role of machine learning in Data Science: A detailed study
Revathi S
Researcher/Data Scientist
Abstract- The machine learning empowers data science to reduce human efforts and become a most valuable asset for business needs through pattern recognition, prediction, analysis and efforts. Now-a-days, organizations really emphasize using data to improve their product needs, where machine learning makes the day of Data Scientist easier by automating the task, and by analyzing enormous amount of data which proves that Data scientist should have in-depth knowledge of Machine learning to improve their prediction process. Machine learning is a subset of Artificial Intelligence, a set of algorithms which trains machine or computers the ability to predict the data on their own. In this paper, a detailed overview of different structures of Data Science and address the impact of machine learning on steps such as Data Collection, Data Preparation, Training the model, Model Evaluation and Prediction. Also, a study on detailed 3 keys on machine learning algorithms such as Classification, regression and clustering is been discussed in this paper.
Keywords- Structure of Data Science, Machine learning, Classification, Regression and Clustering
I.INTRODUCTION
In recent years the phrase Data Science has become buzz word in all industry. Data science is field of study that involves processing large data to obtain insights and valuable information from data. It comprises different fields of expertise and skills to solve and optimize the process. Data Science is a multi-faceted interdisciplinary field of study with Computer/IT, Mathematics/Statistics and Business need/Domain Knowledge [1]. Further, these three domains separately result in a variety of careers as Software (combining computer Science and Business need), Research (Combining Business need and Mathematics) and Machine learning (combining Computer Science and Mathematics). With these areas Data Scientist can maximize their performance by interpreting data and providing innovative solution and achieves improvements in prediction [2].
Machine learning is the field of intersecting computer Science, mathematics and statistics. It is used to identify patterns, recognize behaviors, and make decisions from data with minimal human intervention. It is a method of data analysis that automates data collection, data preparation, feature engineering, training the model, and eventually model evaluation and prediction [3]. Machine learning allows data scientists to implement very complex models, such as neural networks or support vector machines, and an ensemble of simple models like gradient boosting, random forests and decision trees. These complex models can be captured