MACHINE LEARNING FOR DATA SCIENCE - USING ML ALGORITHMS FOR PREDICTIVE MODELING

Dilip Siddareddy · Dr. Haewon Byeon · Purvi Makwana · Dr. Vaibhav Bhatnagar

Oct 2023 · Xoffencerpublication

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203

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About this ebook

Because of the advancements that have been made in machine learning, the world is being changed in ways that are difficult to conceive. If you stop for a second and take a good look around, you'll see that the area of data science is everywhere you turn. Take, for example, Alexa from Amazon; she is an artificial intelligence that has been developed to be as simple and straightforward to use as is humanly conceivable. There are many other digital assistants similar to Alexa, such as Google Assistant, Cortana, and so on. Alexa is not the only one of its sort. Therefore, the question of why they were formed in the first place is the most crucial one to ask; the question of how they developed is the second most important one to ask. In any event, we are going to make an attempt to study each and every one of these issues, and we are also going to make an effort to devise answers that are both logical and technological in nature. Within the scope of this discussion, the question that has to be inquired about first and foremost is, "What exactly are Machine Learning and Data Science?" A widespread misconception is that data science and machine learning are interchangeable terms for the same thing. Those people do have a point, to some extent, considering that data science is nothing more than taking a huge amount of data and analyzing it using a variety of machine learning approaches, methodologies, and technologies. Therefore, in order to become an expert in data science, you need to have a solid understanding of mathematics and statistics, in addition to a profound comprehension of the area that you intend to specialize in. To be more specific, what does it mean to have "subject expertise"? Subject expertise is nothing more than the knowledge necessary about a given topic in order to be able to abstract and calculate the data that pertains to that field, as the name of this type of expertise indicates. In a nutshell, these three concepts are considered as the foundations of data science, and if you are successful in mastering all of them, then you should rejoice yourself because you have achieved the level of an A-level data scientist.

About the author

Dilip Siddareddy is a Microsoft Certified Data Engineer with over long years of diverse experience spanning areas across Data Migration from on-prem to Azure Cloud, building data platforms on Cloud, Data warehousing, Data analytics, Data architecture, Data modeling , development of web applications. He collaborated with system architects, design analysts and others to upscale business and industry requirements. He designed ,developed and deployed Java portlets that interacts with SAP using SAP Java Connector and SAP OLE DB. He Designed and developed a solution to provide real time metrics to business and also Implemented BI solution framework for end-to-end business intelligence projects.

Dr. Haewon Byeon received the Dr Sc degree in Biomedical Science from Ajou University School of Medicine. Haewon Byeon currently works at the Department of Medical Big Data, Inje University. His recent interests focus on health promotion, AImedicine, and biostatistics. He is currently a member of international committee for a Frontiers in Psychiatry, and an editorial board for World Journal of Psychiatry. Also, He were worked on 4 projects (Principal Investigator) from the Ministry of Education, the Korea Research Foundation, and the Ministry of Health and Welfare. Byeon has published more than 343 articles and 19 books.

Purvi Makwana I am Purvi Makwana, working as Asst. Professor with Smt. K. D. M. Mahila Mahavidyala, affiliated to RTMNU. I have 8+ yrs of experience in the Education Industry. My Qualifications are MBA – Marketing & IT, NET – Management, PG Diploma in Business Analytics.

Dr. Vaibhav Bhatnagar is working as Assistant Professor in Department of Computer Applications, Manipal University Jaipur. He has teaching experience of 8 years 8 years. His research intrests are Data Science and Machine Learning. He has published more than 50 papers in different indexed journals. He is expertise in R, Orange, Jamovi, Tableau and Smart PLS.

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