ada-boost-classifier

bhataparnak/Machine-Learning-Projects

Various Machine learning algorithms

luuisotorres/Credit-Card-Fraud-Detection

For this project, I used four different classification algorithms to detect fraudulent credit card transactions.

VivekSagarSingh/Probability-of-Credit-card-Default

Classification problem using multiple ML Algorithms

Abir0810/Countries-Condition-Trees-percentage-and-forestation-using-Machine-Learing

This is about machine learning model where there are many algorithms is using to find out best accuracy.

astonglen/Web-Mining-Project

In this data analysis project, we embarked on a comprehensive exploration of Oracle's interview review data scraped from Glassdoor. Our objective was to gain valuable insights into the interview experiences of candidates applying for specific job postings at Oracle.

Jayveersinh-Raj/ML_algorithms_from_scratch

This repository contains some Machine learning algorithms from scratch to better understand how they work, and are implemented under the hood.

Kenner82/Credit_Risk_Analysis

Testing 6 different machine learning models to determine which is best at predicting credit risk.

luuisotorres/EDA-and-Employee-Attrition-Prediction

Exploratory data analysis and machine learning classification models to predict employee attrition.

rahulvictor12/German-Bank-Loan-Defaulter-Prediction

A machine learning project to predict loan defaults in a German bank's customer base. Using the German Credit Risk dataset, it explores key factors contributing to defaults and trains models like Random Forest, GBM, and XGBoost. Includes EDA, data processing, hyperparameter tuning, and model evaluation.

SaadTariq01DataAnalyst/Prediction-of-HouseGrade-Classification

Prediction-of-House-Grade-Classification using python ( Jupyter Notebook)

thirt33n/Grindwall

ML Based Firewall System

cbrito3/Credit_Risk_Analysis

Supervised Machine Learning and Credit Risk

GR8505/Credit_Risk

Performed supervised machine learning using oversampling, undersampling and combination sampling techniques to determine credit risk for bank customers.

matsuch/Capstone-Project-Starbucks

This project is part of the Capstone Project from the Data Science Nanodegree Program by Udacity in collaboration with Starbucks

pbrebner/text-classifier-with-scikit-learn

Classification of IMDB Reviews dataset and News Group dataset using Logistic Regression, Decision Trees, Support Vector Machines, Ada Boost and Random Forest. Methods and Accuracy of each model were compared and reported

RachitaGurudev/Election-Exit-Poll-Prediction

News channel CNBE wants to analyze recent elections. This survey was conducted on 1525 voters with 9 variables. Model is built to predict which party a voter will vote for on the basis of the given information, to create an exit poll that will help in predicting overall win and seats covered by a particular party.

Szymon-Czuszek/Machine-Learning-Algorithms

In this repository, I will share the materials related to machine learning algorithms, as I enrich my knowledge in this field.

vasatodorovic/ToxicityOfMolecules

Predicting toxicity of molecules. Project on course "Data Mining 2"

vasupatelll/Text_Messgae_Spam_Classifier

A Machine Learning Processing with SMS Data to predict whether the SMS is Spam/Ham with various ML Algorithms like MultinomialNB, LogisticRegression, SVC, DecisionTreeClassifier, RandomForestClassifier, KNeighborsClassifier, AdaBoostClassifier, BaggingClassifier, ExtraTreesClassifier, GradientBoostingClassifier, XGBClassifier to compare accuracy.

yasinsametkaraca/breast-cancer-classification

Zauverer/Test-Crime-Analisys

Boston Crime Analisys test.

dhruwsunita/Heart-Disease-Prediction

Heart Disease Prediction Project using machine learning models.

ejaj/transaction-guard

Develop a prediction model capable of learning to detect whether a transaction is fraudulent or a genuine purchase.

henriqueal/predicting-internet-broadband-errors

sangeetsaurabh/Finding-Donors

Finding Donors for CharityML using Gradient Boosting Classifier, Ada Boost Classifier and Logistic Regression

shourya1997/finding_donors

In this project, we will apply supervised learning techniques and an analytical mind on data collected for the U.S. census to help CharityML (a fictitious charity organization) identify people most likely to donate to their cause.

virajbhutada/titanic-survival-prediction

ML project focused on predicting Titanic passenger survival using various algorithms and extensive data analysis techniques. This project includes detailed data visualization and interpretation to uncover key factors affecting survival. By leveraging various ML models the analysis aims to achieve high predictive accuracy.