Advances in AI/ML, Human Biases, Bounded Rationality
Abstract
Artificial intelligence, machine learning, and deep learning all have quite specific definitions, yet they are all frequently used to refer to any kind of contemporary, big-data related processing technique. In this specific way, it is susceptible to the inevitable buzz that comes together with actual advancements in data processing, which the market is unquestionably loving right now. The article focused on even more important issues about how theory and data interact in an effort to style and mimic human behaviour.
References
Arun Velu, P. W. (2021a). Impact of Covid Vaccination on the Globe using data analytics. International Journal of Sustainable Development in Computing Science, 3(2).
Bhatia, V., & Bhatia, G. (2013a). Room temperature based fan speed control system using pulse width modulation technique. International Journal of Computer Applications, 81(5).
Bhatia, V., & Whig, P. (2013b). A secured dual tune multi frequency based smart elevator control system. International Journal of Research in Engineering and Advanced Technology, 4(1), 1163–2319.
Khera, Y., Whig, P., & Velu, A. (2021a). efficient effective and secured electronic billing system using AI. Vivekananda Journal of Research, 10, 53–60.
Lahade, S. v, & Hirekhan, S. R. (2015a). Intelligent and adaptive traffic light controller (IA-TLC) using FPGA. 2015 International Conference on Industrial Instrumentation and Control (ICIC), 618–623.
Mamza, E. S. (2021). Use of AIOT in Health System. International Journal of Sustainable Development in Computing Science, 3(4), 21–30.
Nadikattu, R. R. (2014a). Content analysis of American & Indian Comics on Instagram using Machine learning. International Journal of Creative Research Thoughts (IJCRT), ISSN, 2320–2882.
Rupani, A., Whig, P., Sujediya, G., & Vyas, P. (2017a). A robust technique for image processing based on interfacing of Raspberry-Pi and FPGA using IoT. 2017 International Conference on Computer, Communications and Electronics (Comptelix), 350–353.
Sharma, A., Kumar, A., & Whig, P. (2015b). On the performance of CDTA based novel analog inverse low pass filter using 0.35 µm CMOS parameter. International Journal of Science, Technology & Management, 4(1), 594–601.
Tomar, U., Chakroborty, N., Sharma, H., & Whig, P. (2021). AI based Smart Agricuture System. Transactions on Latest Trends in Artificial Intelligence, 2(2).
Velu, A., & Whig, P. (2021a). Protect Personal Privacy And Wasting Time Using Nlp: A Comparative Approach Using Ai. Vivekananda Journal of Research, 10, 42–52.
Whig, P. (2019a). A Novel Multi-Center and Threshold Ternary Pattern. International Journal of Machine Learning for Sustainable Development, 1(2), 1–10.
Whig, P. (2019d). Exploration of Viral Diseases mortality risk using machine learning. International Journal of Machine Learning for Sustainable Development, 1(1), 11–20.
Whig, P., & Ahmad, S. N. (2011a). On the performance of ISFET-based device for water quality monitoring. Int’l J. of Communications, Network and System Sciences, 4(11), 709.
Whig, P., & Ahmad, S. N. (2012a). A CMOS integrated CC-ISFET device for water quality monitoring. International Journal of Computer Science Issues, 9(4), 1694–1814.
Whig, P., & Ahmad, S. N. (2012f). Performance analysis of various readout circuits for monitoring quality of water using analog integrated circuits. International Journal of Intelligent Systems and Applications, 4(11), 103.
Whig, P., & Ahmad, S. N. (2013a). A novel pseudo-PMOS integrated ISFET device for water quality monitoring. Active and Passive Electronic Components, 2013.
Whig, P., & Ahmad, S. N. (2014a). Development of economical ASIC for PCS for water quality monitoring. Journal of Circuits, Systems and Computers, 23(06), 1450079.
Whig, P., & Ahmad, S. N. (2014c). Simulation of linear dynamic macro model of photo catalytic sensor in SPICE. COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering.