Converting digital text to handwriting is a simple process because of the abundance of software and websites that do it, like texttohandwriting.com. The Text to Handwriting Converter is a free artificial intelligence-based tool that translates computer text into handwritten text with ease. An individual's handwriting format is saved as an input, converted into text, and then shown as an output. Image processing techniques can be used to process the handwriting. It is possible to use the alphabets of specific languages, such as Tamil (தமிழ்), English, etc. The text of the input is finally displayed in the user's unique handwriting style. It will be useful in numerous ways, including helping the students who have been injured during an accident and it will also reducing the need for paper. Instead of using paper, we can preserve it and refer to it whenever needed. The primary goal of this project is to convert digital text into user handwriting in Tamil (தமிழ்), as it is the oldest language in India and there are currently no websites or apps that accomplish this specifically in Tamil (தமிழ்). There are 247 Tamil (தமிழ்) letters, which are divided into four groups: uyireluttu (உயிரெழுத்து) (12), meyyeluttu (ரெய்ரயழுத்து) (18), uyirmeyyeluttu (உயிெ்ரெய்ரயழுத்து) (216), and finally ayutha eluttu (ஆய்த எழுத்து) (1). A database is created using the handwriting of the person whose handwriting is being converted. These databases consist solely of 247 letters written in that person's handwriting.

social media is being notably used these days. This has reflected in a sort of coercion known as cyberbullying. Bullies use vivid community spots to assault victims with obnoxious Feedback and posts. This has been so ruinous that numerous youngsters suffer despair, commit self-murder, lose their tone of confidence, and plenty less. With obscurity and a deficit of Supervision this form of bullying has advanced exponentially. It is also veritably delicate and tough to show similar times. This leads us to discover a way to help mortal beings out and shield them from similar vulnerable assaults. Machine Learning has vivid algorithms that help us in detecting cyber-bullying with many Algorithms outperforming the others there through abecedarian us to the First- class set of regulations.

The breast cancer prediction is essential for effective treatment and management of the disease. Using data mining techniques to develop predictive models can assist in identifying patients at high risk of developing breast cancer, allowing for early detection and treatment. Early detection has been shown to improve patient outcomes and survival rates. The proposed system for breast cancer prediction involves two main techniques: Linear Discriminant Analysis (LDA) based feature extraction and hyperparameter tuned LSTM-XGBoost based hybrid modelling. The LDA is used to extract the features from the input data that can be trained using a hybrid model such as LSTM and XGBoost. The hyperparameters of both models are optimized using cross-validation techniques to achieve high accuracy in breast cancer prediction. Overall, this proposed system has achieved an accuracy and efficiency of breast cancer prediction than existing.