Advanced Interdisciplinary Applications of Machine Learning Python Libraries for Data Science

Advanced Interdisciplinary Applications of Machine Learning Python Libraries for Data Science
Author :
Publisher : IGI Global
Total Pages : 321
Release :
ISBN-10 : 9781668486986
ISBN-13 : 1668486989
Rating : 4/5 (989 Downloads)

Book Synopsis Advanced Interdisciplinary Applications of Machine Learning Python Libraries for Data Science by : Biju, Soly Mathew

Download or read book Advanced Interdisciplinary Applications of Machine Learning Python Libraries for Data Science written by Biju, Soly Mathew and published by IGI Global. This book was released on 2023-09-13 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: The world is approaching a point where big data will start to play a beneficial role in many industries and organizations. Today, analyzing data for new insights has become an everyday norm, increasing the need for data analysts to use efficient and appropriate tools to provide quick and valuable results to clients. Existing research in the field currently lacks a full coverage of all essential algorithms, leaving a knowledge void for practical implementation and code in Python with all needed libraries and links to datasets used. Advanced Interdisciplinary Applications of Machine Learning Python Libraries for Data Science serves as a one-stop book to help emerging data scientists gain hands-on skills needed through real-world data and completely up-to-date Python code. It covers all the technical details, from installing the needed software to importing libraries and using the latest data sets; deciding on the right model; training, testing, and evaluating the model; and including NumPy, Pandas, and matplotlib. With coverage on various machine learning algorithms like regression, linear and logical regression, classification, support vector machine (SVM), clustering, k-nearest neighbor, market basket analysis, Apriori, k-means clustering, and visualization using Seaborne, it is designed for academic researchers, undergraduate students, postgraduate students, executive education program leaders, and practitioners.


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