Reinforcement Learning in Data Science: Studying reinforcement learning techniques applied in data science tasks such as recommendation systems and optimization
Keywords:
Reinforcement Learning, Data ScienceAbstract
Reinforcement Learning (RL) has emerged as a powerful paradigm for training intelligent agents to make sequential decisions. In the realm of Data Science, RL techniques are increasingly being applied to tackle complex problems such as recommendation systems and optimization tasks. This paper provides a comprehensive overview of the application of RL in Data Science, exploring its principles, algorithms, and real-world applications. We discuss the challenges and opportunities in using RL for data-driven decision-making and highlight the key research directions in this rapidly evolving field.
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Vemoori, Vamsi. "Transformative Impact of Advanced Driver-Assistance Systems (ADAS) on Modern Mobility: Leveraging Sensor Fusion for Enhanced Perception, Decision-Making, and Cybersecurity in Autonomous Vehicles." Journal of AI-Assisted Scientific Discovery 3.2 (2023): 17-61.
Ponnusamy, Sivakumar, and Dinesh Eswararaj. "Navigating the Modernization of Legacy Applications and Data: Effective Strategies and Best Practices." Asian Journal of Research in Computer Science 16.4 (2023): 239-256.
Pulimamidi, Rahul. "Emerging Technological Trends for Enhancing Healthcare Access in Remote Areas." Journal of Science & Technology 2.4 (2021): 53-62.
Tillu, Ravish, Muthukrishnan Muthusubramanian, and Vathsala Periyasamy. "From Data to Compliance: The Role of AI/ML in Optimizing Regulatory Reporting Processes." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.3 (2023): 381-391.
K. Joel Prabhod, “ASSESSING THE ROLE OF MACHINE LEARNING AND COMPUTER VISION IN IMAGE PROCESSING,” International Journal of Innovative Research in Technology, vol. 8, no. 3, pp. 195–199, Aug. 2021, [Online]. Available: https://ijirt.org/Article?manuscript=152346
Tatineni, Sumanth. "Applying DevOps Practices for Quality and Reliability Improvement in Cloud-Based Systems." Technix international journal for engineering research (TIJER)10.11 (2023): 374-380.
Perumalsamy, Jegatheeswari, Chandrashekar Althati, and Lavanya Shanmugam. "Advanced AI and Machine Learning Techniques for Predictive Analytics in Annuity Products: Enhancing Risk Assessment and Pricing Accuracy." Journal of Artificial Intelligence Research 2.2 (2022): 51-82.
Venkatasubbu, Selvakumar, Jegatheeswari Perumalsamy, and Subhan Baba Mohammed. "Machine Learning Models for Life Insurance Risk Assessment: Techniques, Applications, and Case Studies." Journal of Artificial Intelligence Research and Applications 3.2 (2023): 423-449.
Mohammed, Subhan Baba, Bhavani Krothapalli, and Chandrashekar Althat. "Advanced Techniques for Storage Optimization in Resource-Constrained Systems Using AI and Machine Learning." Journal of Science & Technology 4.1 (2023): 89-125.
Krothapalli, Bhavani, Lavanya Shanmugam, and Subhan Baba Mohammed. "Machine Learning Algorithms for Efficient Storage Management in Resource-Limited Systems: Techniques and Applications." Journal of Artificial Intelligence Research and Applications 3.1 (2023): 406-442.
Devan, Munivel, Chandrashekar Althati, and Jegatheeswari Perumalsamy. "Real-Time Data Analytics for Fraud Detection in Investment Banking Using AI and Machine Learning: Techniques and Case Studies." Cybersecurity and Network Defense Research 3.1 (2023): 25-56.
Althati, Chandrashekar, Jegatheeswari Perumalsamy, and Bhargav Kumar Konidena. "Enhancing Life Insurance Risk Models with AI: Predictive Analytics, Data Integration, and Real-World Applications." Journal of Artificial Intelligence Research and Applications 3.2 (2023): 448-486.
Pelluru, Karthik. "Enhancing Security and Privacy Measures in Cloud Environments." Journal of Engineering and Technology 4.2 (2022): 1-7.
Pakalapati, Naveen, Bhargav Kumar Konidena, and Ikram Ahamed Mohamed. "Unlocking the Power of AI/ML in DevSecOps: Strategies and Best Practices." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.2 (2023): 176-188.
Katari, Monish, Musarath Jahan Karamthulla, and Munivel Devan. "Enhancing Data Security in Autonomous Vehicle Communication Networks." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.3 (2023): 496-521.
Krishnamoorthy, Gowrisankar, and Sai Mani Krishna Sistla. "Exploring Machine Learning Intrusion Detection: Addressing Security and Privacy Challenges in IoT-A Comprehensive Review." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.2 (2023): 114-125.
Reddy, Sai Ganesh, et al. "Harnessing the Power of Generative Artificial Intelligence for Dynamic Content Personalization in Customer Relationship Management Systems: A Data-Driven Framework for Optimizing Customer Engagement and Experience." Journal of AI-Assisted Scientific Discovery 3.2 (2023): 379-395.
Modhugu, Venugopal Reddy, and Sivakumar Ponnusamy. "Comparative Analysis of Machine Learning Algorithms for Liver Disease Prediction: SVM, Logistic Regression, and Decision Tree." Asian Journal of Research in Computer Science 17.6 (2024): 188-201.
Prabhod, Kummaragunta Joel. "Advanced Machine Learning Techniques for Predictive Maintenance in Industrial IoT: Integrating Generative AI and Deep Learning for Real-Time Monitoring." Journal of AI-Assisted Scientific Discovery 1.1 (2021): 1-29.
Tatineni, Sumanth, and Karthik Allam. "Implementing AI-Enhanced Continuous Testing in DevOps Pipelines: Strategies for Automated Test Generation, Execution, and Analysis." Blockchain Technology and Distributed Systems 2.1 (2022): 46-81.
Sadhu, Ashok Kumar Reddy, and Amith Kumar Reddy. "A Comparative Analysis of Lightweight Cryptographic Protocols for Enhanced Communication Security in Resource-Constrained Internet of Things (IoT) Environments." African Journal of Artificial Intelligence and Sustainable Development 2.2 (2022): 121-142.
Makka, A. K. A. “Optimizing SAP Basis Administration for Advanced Computer Architectures and High-Performance Data Centers”. Journal of Science & Technology, vol. 1, no. 1, Oct. 2020, pp. 242-279, https://thesciencebrigade.com/jst/article/view/282.
