Machin Learning Full Algorithm (Linear Regression, Decision tree, Random forest, Neural network ,Logistic regression ,Support vector machine ,Naive Bayes ,Clustering, XGBoost,DBscan,KMeans)

kaggle-data-project

This analysis aims to determine the best model for predicting the electrical energy output. The evaluation metric used was the determination coefficient (R-squared).

Classifying customers using Logistic Regression

This group project aims to predict the arrest of different types of crime given a specific input (day/ location/etc.) using machine learning models.

This notebook is a study on the sales of newspapers of a local stand, with intention to predict the newspaper sales performance based on the different features available. For this, 4 sklearn models are applied: Linear Regression, Lasso Regression, Ridge Regression and Elastic Net Regression.

Comparison of Self Implemented Linear Regression and Sklearn Linear Regression