This paper propounds the design and development of a web-based system for a car rental company. It enables admin to rent a car that can be used by a customer on a payment basis. The car information can be added to the system or existing car information can be edited or deleted too by the administrator. The GSM/GPS based content alert for car rental system making the car available for every common man with a minimum cost and effective use of time, Therefore, this application helps the customers to be comfortable and to have the privacy ride as traveling became the part of life. This system makes processing tasks easier and eliminates the traditional record-keeping process. Hence this system enhances the car and customer management and provides customer satisfaction thereby maintaining customer retention.
The proposed project aims to address the escalating concern of cyberbullying on social media platforms by utilizing machine learning classification algorithms, such as Support Vector Machine, to mitigate its effects. To improve the accuracy of the solution, the project will leverage the Natural Language Toolkit to extract features including bigrams, trigrams, n-grams, and unigrams. To evaluate the efficacy of this approach in detecting cyberbullying in tweets, a comparison will be conducted against baseline features and alternative machine learning algorithms. However, it is crucial to consider ethical implications when employing machine learning algorithms to minimize false positives and safeguard innocent individuals from potential harm. In essence, this project holds promise in advancing the development of robust tools for identifying and preventing cyberbullying on social media platforms, a pressing issue in our modern digital era.
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