Adaboost, short for Adaptive Boosting, is a popular and powerful ensemble learning algorithm used in machine learning.

Write a code to implement AdaBoost algorithm using decision stump to learn strong classifier

Machine Learning models compared to find the strongest predictor for credit risk

Adaboost Neural Network And Cyclopean View For No-reference Stereoscopic Image Quality Assessment

Language detector - Classification Algorithm

Performing analyses on New York City Airbnb and developing business intelligence for both the hosts and the guests

This project explores the working of various Boosting algorithms and analyzes the results across different algorithms. Algorithms Used are: Random Forest, Ada Boost, Gradient Boost and XG Boost

A classification project to determine if a passenger survived the Titanic crash or not.

A classification project to determine the eligibility of getting a loan after filling an online form

Implementation of Ensemble Learning, Decision Tree, Random Forest, SVM, KNN, Logistic Regression, Bagging, Boosting and Stacking approach to analysis and predict the abnormal and normal behavior of Imbalanced Colon Dataset.

This is my college practice work, where i try to learn and cover all the tree based regression algorithms (preferably in python).

Multiple Moving objects in a surveillance video were detected and tracked using ML models such as AdaBoosting. The obtained results were compared with the results from Kalman Filter.

Use patient health data from MIT's GOSSIS(Global Open Source Severity of Illness Score) to do an experiment, in which we want to evaluate the question of which modeling strategy leads to the most effective predictions.

Real Time Face Recognition with Python and OpenCV2, Create Your Own Dataset and Recognize that. #FreeBirdsCrew

Analyzing factors leading to customers churning; predicting which customers' will churn?

To Detect Sepsis Disease using six Classifiers on clinical data

Bill Gates was once quoted as saying, "You take away our top 20 employees and we [Microsoft] become a mediocre company". This statement by Bill Gates took our attention to one of the major problems of employee attrition at workplaces. Employee attrition (turnover) causes a significant cost to any organization which may later on effect its overal…

In this project, we analyze and compare the performance of various machine learning algorithms (Linear Regression, Decision Tree, AdaBoost, XGBoost, Gradient Boosting and k- Nearest Neighbors) when used to predict hard drive failures using Backblaze data in the year 2018.

CART, K-Means, Apriori, Adaboost, RFE; models using Anti-cancer peptides vs Human proteins

Implementation of various machine learning algorithms from scratch.