Visualizes the data, builds a multi-linear regression model, applies a 10-fold cross-validation resampling method, and evaluates LM, SVM, and KNN model performance using R

Capstone project: machine learning engineer nanodegree

Bible Classification Task

• Addressing the challenges faced by Farmers developed Farmer.ai website for real-time crop recommendations Fertilizer and Pesticide prediction features based on soil and pest. • Empowered farmers with intuitive tools for optimal crop management decisions.

[Project🗂] 영화 데이터를 이용한 KNN, Decision tree, Regression 수행. 관객수, 배우, 투자 비용들을 고려한 영화 기대 수익 예측

Predicting Mobile Plan Cancelation

Objectives: 1) Design a KNN algorithm using R, 2) Summarize classification performance using KNN, linear/quadratic regression and Bayes rule. Training and test data are generated from a bi-variate Gaussian mixture model.

This is a university project for my Data Mining course. This work focuses on a binary classification task (related to CS-GO); which team will win?

Project for the Machine Learning 2021/22 class at the Faculty of Economic Sciences, University of Warsaw. I was responsible for the drug abuse prediction task for which I build logit, probit, KNN and SVM classification models.

Insurance prediction of similar clients with KNN

Applying unsupervised learning algoriths on online shoppers intention data and model building

Short collection of predicting ML model on diabetes patients

A company X required a churn model to mitigate the monetary losses from discounts provided to customers.

Desenvolvimento de um modelo de classificação usando o algoritmo KNN para prever a ocorrência de diabetes, com implantação na plataforma Vercel.

People with cardiovascular disease or who are at high cardiovascular risk (due to the presence of one or more risk factors such as hypertension, diabetes, hyperlipidaemia or already established disease) need early detection and management wherein a machine learning model can be of great help.

*Worked on "Ideal Life Survey" Dataset using different statistical analysis tools to build a machine learning model that predicts the state of satisfaction of a student according to distinct variables like University grades , Background , Number of extra curricular activities...

Product recommendation system based on Artificial Intelligence algorithms

A repository having all data science concepts programmed in R.

Study about salaries in data scientists roles applying the following techniques: QDA, LDA, Naive-Bayes approach, Random Forests, KNN, SVM, (Logistic, Lasso and Ridge) Regression and Elastic Nets. Also, study of the database considering linear, simple and multivariate models.