Synopsis
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.
About the Authors
Soly Mathew Biju CITP CEng FBCS FHEA is a Ph.D. in Computer Science and also an MBA in IT management with 25 years of experience in industry and academia. She is currently an Associate Professor at the Faculty of Engineering and Information Sciences, University of Wollongong in Dubai. Dr Biju is awarded the most prestigious Fellowship by British Computer Society and also has CEng status awarded by Engineering Council (UK). She also has achieved the Chartered IT Professional status which is a symbol of excellence in the field of IT and is also an ISTQB-certified software testing professional. She is also a Fellow Higher Education Academy, UK. HEA Fellowship demonstrates a personal and institutional commitment to professionalism in learning and teaching in higher education. She is the Head of the Global Health and Wellbeing cluster at UOWD. She was nominated for the Teaching Excellence and Research Excellence awards at UOWD on numerous occasions and received the prestigious Teaching Excellence Award in numerous occasions. She was also awarded the prestigious Amity Global Academic Excellence award in 2020. Her research interests include machine learning and AI to improve quality of life, data security, software testing, cryptography, e-learning, innovations in teaching, agile software development, online teaching, network security and programming techniques. She has papers published in reputed journals and books and presented and reviewed papers at national and international conferences and journals. She has been a scientific and organizing committee member and session chair and content chair on various reputed national and international conferences. She has won a number of research grants for her research proposals and is also an author.
Ashutosh Mishra received his B.Tech. in Electronics & Communication Engineering from Uttar Pradesh Technical University, Lucknow, India, in 2008. He completed his M.Tech. in Microelectronics & VLSI Design from the National Institute of Technology, Allahabad, India, in 2011, and his Ph.D. in Electronics Engineering from the Indian Institute of Technology (BHU), Varanasi, India, in 2018. He has served as an Assistant Professor in Electronics & Communication Engineering at the National Institute of Technology, Raipur, India. Dr. Mishra was awarded the Korea Research Fellowship (KRF) in 2019 by the National Research Foundation of Korea through the Ministry of Science & ICT, South Korea. He also worked as a Brain Pool Fellow in the Seamless Transportation Lab at Yonsei University, South Korea. Currently, he is an Assistant Professor in the Department of Electrical & Electronics Engineering at BITS Pilani, Dubai, UAE. His research interests include smart sensors, intelligent systems, autonomous vehicles, convergence technology, and artificial intelligence.
Manoj Kumar completed his Ph.D. from Northcap University and M.Sc. (Information Security and Digital Forensics) from Technological University Dublin, Ireland in 2013. Dr. Kumar has more than 14.5+ years of research, teaching, and corporate experience. Currently, Dr. Kumar holds the position of Associate Professor at the University of Wollongong in Dubai. Dr. Kumar is listed among the top 2% of computer scientists worldwide. He published over 225 research articles in international refereed journals and conferences. He gave 12 patents, delivered four international research-funded projects, and released three authored and forteen edited books. In addition, he acts as an associate editor, guest editor, and editorial board member for various scientific journals. Dr. Kumar is a member of numerous renowned professional bodies, including IEEE, ACM, IAENG, ISTS, and UACEE. His specializations are Digital Forensics, Machine Learning, Information Security, Image Processing, IOT and Networks.
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