Journal of Contemporary Education Theory & Artificial Intelligence                                                               Issue 1 | 2022      
Contemp Edu Theo Artific Intel: 2022; 1(1): 104 | |                                                                   | Full-text PDF
Forecasting Financial Trends Using Time Series Based ML-DL Models for Enhanced Business Analytics
Author(s): Vetrivelan Tamilmani1, Aniruddha Arjun Singh2, Vaibhav Maniar3, Rami Reddy Kothamaram4, Dinesh Rajendran5, Venkata Deepak Namburi6
DOI: 10.71010/2996-4954/JCETAI/104
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Contemp Edu Theo Artific Intel: 2022; 1(1): 103 | |                                                                   | Full-text PDF
Leveraging Artificial Intelligence and Big Data Analytics for Early and Accurate Identification of Heart Diseases from Electronic Health Records
Author(s): Avinash Attipalli1*, Varun Bitkuri2, Raghuvaran Kendyala3, Jagan Kurma4, Jaya Vardhani Mamidala5, Sunil Jacob Enokkaren6
DOI: 10.71010/2996-4954/JCETAI/103
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Contemp Edu Theo Artific Intel: 2022; 1(1): 102 | |                                                                   | Full-text PDF
Leveraging Big Datasets for Machine Learning-Based Anomaly Detection in Cybersecurity Network Traffic
Author(s): Rajiv Chalasani1*, Mukund Sai Vikram Tyagadurgam2, Venkataswamy Naidu Gangineni3, Sriram Pabbineedi4, Mitra Penmetsa5, Jayakeshav Reddy Bhumireddy6
DOI: 10.71010/2996-4954/JCETAI/102
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Contemp Edu Theo Artific Intel: 2022; 1(1): 101 | |                                                                   | Full-text PDF
Efficient Machine Learning Approaches for Intrusion Identification of DDoS Attacks in Cloud Networks
Author(s): Sandeep Kumar Chundru1*, Srikanth Reddy Vangala2, Ram Mohan Polam3, Bhavana Kamarthapu4, Ajay Babu Kakani5, Sri Krishna Kireeti Nandiraju6
DOI: 10.71010/2996-4954/JCETAI/101
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Contemp Edu Theo Artific Intel: 2021; 1(1): 101 | |                                                                   | Full-text PDF
Real-time Anomaly Detection in Telecom Data Streams: Applying Deep Learning for Network Intrusions, Fraud, and Service Degradation
Author(s): Venu Madhav Nadella*
DOI: 10.71010/2996-4954/jcetai-101
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