A R script that runs Boosted Regression Trees(BRT) on epochs of land use datasets with random points to model land use changes and predict and determine the main drivers of change

Decompose gbm predictions into feature contributions

Machine Learning approach to predicting comment recommendations based on New York Times articles and comments made on those articles.

Une expérimentation autour d'un petit jeu de données de Churn bancaire

R-based project to analyze lyrics entropy by genre and decade. A hand-engineered feature "words-per-unique-word" is introduced and deeply studied. Spotify and Genius APIs are used

In this project, exploratory data analysis was used to identify reasons why employees leave and machine learning methods were used predict employee attrition

Building binary predictors on a heavily imbalanced dataset - exercise on policy cross-selling [kaggle]

Project to produce supervised ML algorithm to predict which customers are likely to leave and produce .Rmd report

One Data Set with multiple Algorithms

h2o is a ML library that can be used with R and Python. Here are some R examples for supervised and unsupervised methods.

Various variable selection methods are explored

The project involves deciding on the mode of transport that the employees prefer while commuting to office. For this, multiple models such as KNN, Naive Bayes, Logistic Regression have been created and explored to check their model performance metrics. Bagging and Boosting modelling procedures have also been applied to create the models.

Deep Learning for Automatic Differential Diagnosis of Primary Central Nervous System Lymphoma and Glioblastoma: Multi-parametric MRI based Convolutional Neural Network Model

The objective of the project is to create a machine learning model. We are doing a supervised learning and our aim is to do predictive analysis to predict median housing price.

Detect Credit Card Fraud with Machine Learning in R

Analysis music on Spotify and predictions of preferences

This project about the GBM classification model on spam email data set and model optimisation.

Single-cell multi-omic profiling of glioblastoma-associated myeloid cells