• Mr. Kapu Sainath Reddy
• Mr. Dr. K.E. Naresh Kumar

The greatest amount of SPIT devices is web-dependent, hence caution must be exercised when using web-based devices. It is typical in the workplace that the SPIT devices set up in an organization can be used to effectively carry out security and protection measures. For instance, wearable technology that gathers and transmits user health information to a connected smartphone should guard against data leaks to preserve privacy. According to market research, 25–30% of employees who are currently at work connect their own SPIT devices to the company network. The fact that SPIT is growing draws both the target audience, or the users, and the attackers as a result. However, when ML becomes more prevalent in various assault scenarios, SPIT devices decide on a defensive plan and the key. parameters for a trade-off between security, privacy, and computation in the security protocols. Instead of affecting a classification model, this work improves the technique such that it can affect a time-series regression model. It may also execute ML models concurrently. The purpose of this suggested research is to evaluate the SPIT device's reliability within the smart home network.

Machine Learning Based Student Performance Prediction using Feedback Method

" Machine Learning Based Student Performance Prediction using Feedback Method", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 7, page no.g189-g192, July-2023, Available :http://www.jetir.org/papers/JETIR2307630.pdf

" Machine Learning Based Student Performance Prediction using Feedback Method", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 7, page no. ppg189-g192, July-2023, Available at : http://www.jetir.org/papers/JETIR2307630.pdf