Quantum Machine Learning: A Modern Approach

This text presents the research into and application of machine learning in quantum computation, known as quantum machine learning (QML). It presents a comparison of quantum machine learning, classical machine learning, and traditional programming, along with the usage of quantum computing, towards improving traditional machine learning algorithms through case-studies.

- Covers the core and fundamental aspects of statistics, quantum learning and quantum machines

- Discusses the basics of machine learning, regression, supervised and un-supervised machine learning algorithms, and artificial neural networks

- Elaborates upon quantum machine learning models, quantum machine learning approaches and quantum classification, boosting.

- Introduces quantum evaluation models, deep quantum learning, ensembles and QBoost

- Presents case studies to demonstrate the efficiency of quantum mechanics in industrial aspects

The text is primarily written for scholars and researchers working in the fields of Computer Science and Engineering, Information Technology, Electrical Engineering, and Electronics and Communication Engineering.

Dr. S. Karthikeyan received his B.E degree in computer science and engineering from Anna University, Chennai, India in the year 2010, his M.E degree in Software engineering from Anna University, Chennai, India in the year 2012. Ph.D. Degree from VIT University, Andhra Pradesh, India in the year Jan 2021. Currently working as an associate professor in computer science and engineering (Artificial intelligence and Machine Learning) at KPR Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India. His research interests include artificial intelligence and machine learning, high-performance computing, cloud and big data analytics, and data sciences. Published 40+ papers in reputed journals, 7 book chapters, and 12+ patents. He is Life member in international professional bodies such as ISTE, IAENG, ISRD, IFERP. Also, he is a Senior Member of IEEE.

Dr. M.Akila is a Principal of KPRIET with, Insatiable appetite for continuous learning and teaching, a Philanthropic leader, a Diligent Researcher, Experienced and insightful academician. As the face and head of the institution, I am responsible for the education that each student under my care receives, effective leadership and overall management of the institution. I am an effective listener, problem solver and responsive to honest feedback for institute improvement. With 27 years of experience, my mission is to enhance the standards of education by providing an excellent, ingenious, learning environment that is rational with the core values of KPRIET. Further, I keep my professional development and learning continuous.
Main research interest is machine learning with applications to computer vision and data science. I am also interested in the efficient implementation of optimization algorithms in engineering problems. An inspiring and motivating committed CSE professor. Actively engaged with professional organizations such as IET and IEEE. Additional secretary in the institution of Green Engineers. Published 3 patents and delivered 32 invited lectures at various institutes. Has facilitated faculty to write research proposals as Dean and R& D and successful in getting 75lakhs worth funding to KPRIET. Received Kalam 2020 award - service to Green technology 2018. Awarded Cambridge International certificate for teachers and trainers level. Recipient of Certificate of Achievement from IGEN. Renowned reviewer Neuro computing, IET Biometrics, IET image processing, IET Electronics letters.

Dr. D. Sumathi is currently serving as a Professor Grade 1-SCOPE at VIT-AP University, Andhra Pradesh. She earned her B.E in Computer Science and Engineering from Bharathiar University in 1994 and her M.E in Computer Science and Engineering from Sathyabama University in 2006, Chennai. She completed her doctoral degree at Anna University, Chennai. With a total of 23 years of experience, including 6 years in the industry and 17 years in the teaching field, she holds the additional responsibility of serving as an Assistant Director of the Software Development Cell, which automates various campus upkeep functionalities.

Dr. D. Sumathi has taken on various administrative roles during her tenure. Her research interests encompass Cloud Computing, Network Security, Data Mining, Natural Language Processing, Machine Learning, Deep Learning, and Theoretical Foundations of Computer Science. She has published numerous papers in reputed international journals and conferences. Furthermore, she has organized several international conferences, acting as a Technical Chair and tutorial presenter. Dr. D. Sumathi is a life member of ISTE and has published book chapters in CRC Press, IGI Global, Springer, IET, and edited books with publishers like CRC and Wiley. In addition to this, she holds patents related to the health sector. Her invited talks on domains such as Machine Learning, Deep Learning, and Big Data Analytics have inspired budding researchers to engage in thoughtful research works and problem statements. Currently, she is guiding five research scholars under research areas in biomedical applications.

Prof. T. Poongodi is currently working as a Professor in the School of Computing Science & Engineering at the Galgotias University, Delhi - NCR, India. She received her Ph.D. degree in Information Technology (Information and Communication Engineering) from Anna University, Tamil Nadu, India. Her current research interests include Network Security, Wireless Ad Hoc and Sensor Networks, Internet of Things (IoT), Data Science, and Blockchain Technology for emerging communication networks. She is CISCO, Oracle Academy, and Structured Query Language certified. Prof. T. Poongodi is the author of over 50+ book chapters including some reputed publishers such as Springer, Elsevier, IET, Wiley, De-Gruyter, CRC Press, IGI global, and 30+ international journals and conferences. She has published 15+ authored/edited books in the areas of Internet of Things, Data Analytics, Blockchain Technology, Artificial Intelligence, Machine Learning, and Healthcare Informatics, published by reputed publishers such as Springer, IET, Wiley, CRC Taylor & Francis, and Apple Academic Press. She adopts a universal and humanistic approach in her academic and research works. In her research, she has undertaken meticulous scientific studies of emerging issues in networking disciplines. She has 17+ years of academic work experience in teaching and multi-disciplinary research. She received awards namely the Research and Innovation award (2019, 2020, 2021), and Excellence in the area of Research & Innovation/ Academic Excellence / Extension Activities (2018-19, 2019-20) from Galgotias University. Prof. T. Poongodi has also received invitations to address international conferences as a keynote speaker. She is the reviewer for international journals, conferences and she has 5 Indian patents also.