Machine Learning

This page contains projects and practicals I undertook to further my understanding of ML concepts and practical applications of it.

Predicting Spread of Wildfires

The goal of the project was to build a machine learning pipeline to predict the spread of wildfires in the northeastern region of Portugal.

article: https://medium.com/@fatima.zohra.siddiqui/predicting-the-spread-of-forest-fires-5ff289088240

code: https://github.com/blipblopblop/Predicting-Spread-of-Wildfires

Building Classification Models

To really understand classification models, real world data sets were undertaken and applied on k - nearest neighbours, logistic regression, decision tree, and support vector machine models to form predictors.

https://github.com/blipblopblop/Building-Classification-Models

Building Regression Models

To understand regression models, real world data sets were undertaken and applied on linear, multiple, polynomial, and non-linear regression.

https://github.com/blipblopblop/Building-Regression-Models