aNALYSIS OF MACHINE LEARNING MODELS FOR PREDICTION OF GRADUATE ADMISSION

I need a python code linear regression, random forest and neural networks without the use of the existing libraries such as linearregression, randomforests, or neural networks to predict if a student can get admission in a university or not. Finally, calculation of mean squared error for each model to compare the accuracy of each. The libraries can be used are numpy, pandas, matplotlib and other basic libraries. The dataset to be used is UCLA admissions dataset from KAGGLE. The code should be written in google collab.