This project predicts wind turbine failure using numerous sensor data by applying classification based ML models that improves prediction by tuning model hyperparameters and addressing class imbalance through over and under sampling data. Final model is productionized using a data pipeline

Website Prediksi Penyakit jantung dengan 5 fitur menggunakan metode KNN,bagging classifier,random forest

Code in which an initial approach to decision trees and bagging will be made, and an attempt will be made to ensure that the model can be trained with any dataset coming from Kaggle (for this, we will again use the 'connect with Kaggle' project).

A Tkinter based ML tool that classifies astronomical entities as Galaxy, Star, and Quasar

Customer Churn Prediction using Machine Learning and Deep learning. With Integration of MLFlow

The project is to analyze the flight booking dataset obtained from a platform which is used to book flight tickets.

Bagging is the term from "Bootstrap Aggregation Algorithm", That is for Low Bias & Low Variance

Analyze the data of Visa applicants, build a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa status recommend a suitable profile for the applicants for whom the visa should be certified or denied.

R | Classification Project

Intro to Machine Learning Assignment 3

The objective is to analyze voter behavior based on demographic and opinion-based variables and build a classification model that can predict which party a voter will vote for. This model is used to simulate an exit poll.

Project for the "Computational and Statistical Learning" course.

Some process on Shatel dataset.

This assignment dives deeper into machine learning by implementing and evaluating ensemble methods. The notebook covers techniques like bagging and boosting, using models such as Random Forests and AdaBoost. It includes performance comparisons, visualizations, and insights into how ensemble learning improves model accuracy and robustness.

A machine learning application, deployed using Flask, is designed to identify the presence of heart disease in patients by analyzing various medical features.

Crop Recommendation System is a powerful tool for enhancing agricultural decision-making. By leveraging data-driven insights, it empowers farmers to maximize yield and ensure sustainable practices.

This project aims to predict the success of crowdfunding campaigns using machine learning models: Ensemble Learning, Naive Bayes, and Support Vector Machine (SVM).

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