Big Data Using Machine Learning and Deep Learning
Keywords:
Machine, learning, artificial, intelligence, Big DataAbstract
A process of obtaining knowledge for the purpose of making intelligent decisions, machine learning is a form of artificial intelligence called machine learning. In terms of scientific breakthroughs and the generation of value, Big Data has a significant impact. Several applications of machine learning in Big Data are discussed in this paper, along with the methodologies that are used in machine learning and the primary technologies that are used in Big Data. Discussion is held regarding the difficulties that arise when applying machine learning to Big Data. There is also a presentation of some new techniques and technological advancements in the field of machine learning in Big Data.
References
C. L. P. Chen, C. Y. Zhang, “Data-intensive applications, challenges, techniques and technologies: A survey on Big Data”, Information Sciences, Vol. 275, No. 10, pp. 314-347, August 2014.
K. M. Tarwani, S. S. Saudagar, H. D. Misalkar, “Machine Learning in Big Data Analytics: An Overview”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 5, No. 4, pp. 270-274, April 2015.
J. Dean, “Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners”, John Wiley & Sons, Inc., 2014.
U. Jaswant and P.N. Kumar, “Big Data Analytics: A Supervised Approach for Sentiment Classification Using Mahout: An Illustration”, International Journal of Applied Engineering Research, Vol. 10, No. 5, pp. 13447-13457, 2015.
Y. Demchenko, P. Grosso, C. De Laat, P. Membrey, “Addressing Big Data Issues in Scientific Data Infrastructure”, 2013 International Conference on Collaboration Technologies and Systems (CTS), San Diego, CA, USA, pp. 48-55, May 2013.
D. E. O'Leary, “'Big Data', the 'Internet of Things' and the 'Internet of Signs'”, Intelligent Systems in Accounting, Finance and Management, Vol. 20, pp. 53-65, 2013.
H. V. Jagadish, A. Labrinidis, Y. Papakonstantinou, et al., “Big Data and Its Technical Challenges”, Communications of the ACM, Vol. 57, No. 7, pp. 86-94, 2014.
A. Zaslavsky, C. Perera and D. Georgakopoulos, “Sensing as a Service and Big Data”, International Conference on Advances in Cloud Computing (ACC), Bangalore, India, pp. 1-8, July 2012
M. Turk, “A chart of the big data ecosystem”, take 2, 2012.
R. Zafarani, M. A. Abbasi, H. Liu. “Social Media Mining: An Introduction”, Cambridge University Press, UK, 2014.
S. Singh and G. Jagdev, "Execution of Big Data Analytics in Automotive Industry using Hortonworks Sandbox," 2020 Indo – Taiwan 2nd International Conference on Computing, Analytics and Networks (Indo-Taiwan ICAN), Rajpura, India, 2020, pp. 158-163, doi: 10.1109/Indo-TaiwanICAN48429.2020.9181314.
Singh, S., Jagdev, G. Execution of Structured and Unstructured Mining in Automotive Industry Using Hortonworks Sandbox. SN COMPUT. SCI. 2, 298 (2021).
Brar, T. P. S. (2021). Digital Marketing Performance: Understanding the Challenges and Measuring the Outcomes. In Big Data Analytics for Improved Accuracy, Efficiency, and Decision Making in Digital Marketing (pp. 51-63). IGI Global.
Mehta, S., Kukreja, V., Bhattacherjee, A., & Brar, T. P. S. (2023, April). Predicting Rice Leaf Disease Outbreaks using CNN-SVM Models: A Machine Learning Approach. In 2023 IEEE International Conference on Contemporary Computing and Communications (InC4) (Vol. 1, pp. 1-5). IEEE.
Banerjee, D., Kukreja, V., Gupta, A., Singh, V., & Brar, T. P. S. (2023, August). CNN and SVM-based Model for Effective Watermelon Disease Classification. In 2023 3rd Asian Conference on Innovation in Technology (ASIANCON) (pp. 1-6). IEEE.
Sharma, R. K., Brar, T. P. S., & Gandhi, P. (2021). Defense and Isolation in the Internet of Things. Internet of Things in Business Transformation: Developing an Engineering and Business Strategy for Industry 5.0, 141-168.
Brar, T. P. S. (2018). Business intelligence in banking: a study of bi technology implementation and challenges. CGC International Journal of Contemporary Technology and Research, 1(1).
Lata, S., & Singh, D. (2022, April). A Hybrid Approach for Cloud Load Balancing. In 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) (pp. 548-552). IEEE.
Lata, S., & Singh, D. (2022). Intrusion detection system in cloud environment: Literature survey & future research directions. International Journal of Information Management Data Insights, 2(2), 100134.
Lata, S., & Singh, D. (2022, October). Cloud simulation tools: A survey. In AIP Conference Proceedings (Vol. 2555, No. 1). AIP Publishing.
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