Write the code from scratch without using the Regression, Random Forests or Neural networks libraries.

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Code written in Python for Linear Regression, Random Forests and Neural Networks Model to predict if a student will get admission in a university or not. The code should be written from scratch without using the Regression, Random Forests or Neural networks libraries. Use pandas, numpy, matplotlib etc. But not the already existing ML model libraries. Use for loops and other things. The dataset to be used is the UCLA ADMISSIONS DATASET from Kaggle.

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