theonugraha

Price-Predict-using-Linear-Regression-on-The-Ride-Hailing-Platform

This project aims to predict the price of rides on the ride-hailing platform of the company Uber & Lyft in Boston, so we can know the price if we want to go to somewhere based on distance, hour, day, temperature, name (Uber or Lyft) and cab type.

Credit-Card-Default-Prediction

This project aims to predict credit card customer defaults with an algorithm that has the best accuracy rate.

Vehicle-Type-Recognition-using-CNN-and-ElasticNet

The main objective of this project is to build a machine learning model that can distinguish between four categories of vehicles: cars, trucks, buses, and motorcycles using Convolutional Neural Networks (CNN) and ElasticNet.

Customer-Segmentation-Machine-Learning

The goal of this project is to implement a clustering-based customer segmentation technique using machine learning in the financial industry.

Income-Prediction-

This project aims to predict income based on its group using Logistic Regression and Support Vector Classification methods.

Indonesia-Rainfall-Trend-2020

Car-Price-Prediction-using-Multiple-Linear-Regression-and-clustering-using-KMeans

This project aims to predict car prices using Multiple Linear Regression and clustering using K-Means Clustering.

Credit-Card-Customer-Segmentation-Machine-Learning

The purpose of this project is to apply machine learning techniques to segment credit card customers using Dimensional Reduction and K-Means Clustering.

Credit-Card-Fraud-Detection

This project aims to create machine learning to detect credit card fraud.

Global-YouTube-Statistics-2023

This project aims to analyze the Global YouTube Statistics 2023 and create clusters using the K-Means algorithm.

theonugraha/Superstore-Sales-Analysis

theonugraha/Customer-Segmentation-Machine-Learning

The goal of this project is to implement a clustering-based customer segmentation technique using machine learning in the financial industry.

theonugraha/Credit-Card-Customer-Segmentation-Machine-Learning

The purpose of this project is to apply machine learning techniques to segment credit card customers using Dimensional Reduction and K-Means Clustering.

theonugraha/Vehicle-Type-Recognition-using-CNN-and-ElasticNet

The main objective of this project is to build a machine learning model that can distinguish between four categories of vehicles: cars, trucks, buses, and motorcycles using Convolutional Neural Networks (CNN) and ElasticNet.

theonugraha/Indonesia-Rainfall-Trend-2020

theonugraha/Price-Predict-using-Linear-Regression-on-The-Ride-Hailing-Platform

This project aims to predict the price of rides on the ride-hailing platform of the company Uber & Lyft in Boston, so we can know the price if we want to go to somewhere based on distance, hour, day, temperature, name (Uber or Lyft) and cab type.

theonugraha/Credit-Card-Default-Prediction

This project aims to predict credit card customer defaults with an algorithm that has the best accuracy rate.

theonugraha/Credit-Card-Fraud-Detection

This project aims to create machine learning to detect credit card fraud.

theonugraha/Income-Prediction-

This project aims to predict income based on its group using Logistic Regression and Support Vector Classification methods.

theonugraha/Car-Price-Prediction-using-Multiple-Linear-Regression-and-clustering-using-KMeans

This project aims to predict car prices using Multiple Linear Regression and clustering using K-Means Clustering.

theonugraha/Global-YouTube-Statistics-2023

This project aims to analyze the Global YouTube Statistics 2023 and create clusters using the K-Means algorithm.

theonugraha/Non-Graded-Challenge-8

theonugraha/Non-Graded-Challenge-7

theonugraha/Non-Graded-Challenge-6

theonugraha/Non-Graded-Challenge-5

theonugraha/Non-Graded-Challenge-4

theonugraha/Non-Graded-Challenge-3

theonugraha/Non-Graded-Challenge-1

theonugraha/Non-Graded-Challenge-2