Avaliação do estado de aplicativos Android entre os anos de 2010 e 2018 presentes na Google Play Store por técnicas de visualização de dados. Identificação de parâmetros potencialmente importantes para o número de instalações de um aplicativo e seu envolvimento com a precificação (gratuito ou pago), através do uso de técnicas de machine learning.

SDS course assignments

Classification of Bankruptcy Database to Perform Classification with Machine Learning

This model performs regression on the given Dataset, and shows the best out of four machine learning Models with plots.

Decision Tree and K-Nearest Neighbors using Heart Disease dataset

Predicting dwelling type using Decision Tree algorithm on a surveyed data set. The project includes feature selection, pre-processing and model evaluation.

American loan default analysis

I am interested in exploring machine learning techniques to predict the outcome of a European soccer game using game and player information collected. The generated predictive model will be able to predict the outcome of a game as Win, Loss or Draw for the home team. This model will use various attributes that are calculated each year for both h…

HR Analytics and Employee Performance IBM use of model classifiers to predict whether an employee is likely to quit or not

This is a rainfall prediction classification using R programming.

Cognifyz Technologies Data Science Internship project on Restaurant Data Analysis to explore insights and build predictive models.

Paper, code, and data on "Commentary on 'Targeting with machine learning: An application to a tax rebate program in Italy'"

Using Decision Tree Algorithm on iris dataset and performing data analysis and prediction functions on it

CAP5615 Intro to Neural Networks class at FAU, Summer 2018

for the publication "A network approach to understanding interspecific interactions within a multi-species flock " (in prep)

Decision tree and forward chaining algorithms implemented in pure R.

위치 데이터를 활용해 점심 식사 위치를 예측하는 프로젝트

Using advanced machine learning algorithms to predict Home Warranty Renewal success in R.

Classification of Obesity Status in Indonesia Using XGBoost & ADASYN-N Method

The objective of the project is to demonstrate a model which can identify risky bank loans i.e., the one's likely to default. In doing so, I have implemented decision tree algorithm and applied boosting to further make the code more accurate.