R package for the simulation of the prior distribution of bayesian trees by Chipman et al. (1998).

Nations Flags Classification & Clustering project. 🎏

🌳 Predicting a wildfire's severity using classification models

Leverage external data and non-traditional methods to accurately assess and shortlist candidates with the relevant skillsets, experience and psycho-emotional traits, and match them with relevant job openings to drive operational efficiency and improve accuracy in the matching process

Prediction of Heart Attacks Using Different algorithms in R.

Final Project for Higher Diploma in Data Analytics at National College of Ireland

Data Analysis and Decision Making Project using R

Build a model that will help them identify the potential customers who have a higher probability of purchasing the loan.

A data set of 30000 records and 24 variables containing information on defaults, demographic factors, credit data, delinquency, repayment and billed amounts of a credit card client in Taiwan from April 2005 to September 2005. The objective was to apply statistical, data visualization and Machine learning techniques (supervised and unsupervised) …

It is important that credit card companies are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase. Here, the aim is to analyze the dataset and detect the fradulent transactions.

Statistical analysis on calcium concentration during dialysis

The data at hand is of flight satisfaction survey along with the customer flight information, the task at hand is to build a model that predicts satisfaction/dissatisfaction given the various attributes

Leverage external data and non-traditional methods to accurately assess and shortlist candidates with the relevant skillsets, experience and psycho-emotional traits, and match them with relevant job openings to drive operational efficiency and improve accuracy in the matching process

HR Employee Attrition Data file is provided: To Build Neural Network and CART model on same:

Develop a logistic regression model and a CART model to predict diabetes outcome

On creating synthetic, representative data from real, sensitive inputs

Data Analytics Programs

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.

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 housing price.