Fast boosting with AdaBoost and Bandit

Supervised learning and unsupervised in R, with a focus on regression and classification methods.

TP2 de Aprendizado de Máquina (2021/1) no DCC/UFMG.

This repository consists of projects on Big Data and Data Analytics as a part of our curriculum for PGDM- BDA (4th Term) at FORE School of Management, New Delhi.

Chapter 8 Assignment Bagging vs Boosting vs. Random Forest

Implementation of popular ensembles methods in C++

Linear and Logistic Regression on Airbnb dataset

Analytics Vidhya AmExpert ML Competition

Logisitc Regression - A Binary Classification Method

Analyze the data and come up with a predictive model to determine if a customer will leave the credit card services or not and the reason behind it

This notebook explores fraud detection using various machine learning techniques.

Implementing random forest models in R with bagging and boosting.

This is Kaggle challenge for house prediction, it has alot of missing values which needs to be cleaned. i have used Regression ,Boosting, and Deep Neural network and tuning them.

Algorithms from scratch to know how the algorithms work.

Using Logistics, Classification, and KNN modelling to predict if a credit card account will default.

It is a subset of variables from a study carried out in 1988 in different regions of the world to predict the risk of suffering a heart-related disease.

We have a data of retail transactions over two year. Apart from data analysis and visualization, a regression model is developed to predict the price of retail items belonging to different categories. Foretelling the Retail price can be a daunting task due to the huge datasets with a variety of attributes ranging from Text, Numbers(floats, integ…

Machine Learning Jupyter notebook exercises created as a TA at Santa Clara University

Coursework, Computational Machine Learning II, BSE, Term 2, Class of 2022