ada-boost-classifier
There are 27 repositories under ada-boost-classifier topic.
FreeBirdsCrew/Real-Time_Face_Recognition
Real Time Face Recognition with Python and OpenCV2, Create Your Own Dataset and Recognize that. #FreeBirdsCrew
luuisotorres/Credit-Card-Fraud-Detection
For this project, I used four different classification algorithms to detect fraudulent credit card transactions.
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.
bhataparnak/Machine-Learning-Projects
Various Machine learning algorithms
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.
thirt33n/Grindwall
ML Based Firewall System
VivekSagarSingh/Probability-of-Credit-card-Default
Classification problem using multiple ML Algorithms
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.
luuisotorres/EDA-and-Employee-Attrition-Prediction
Exploratory data analysis and machine learning classification models to predict employee attrition.
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
SaadTariq01DataAnalyst/Prediction-of-HouseGrade-Classification
Prediction-of-House-Grade-Classification using python ( Jupyter Notebook)
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.
trevortnguyen/Customer-Segmentation-Classification
Classifying customers into segments
vasatodorovic/ToxicityOfMolecules
Predicting toxicity of molecules. Project on course "Data Mining 2"
vasupatelll/Email_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 an
Zauverer/Test-Crime-Analisys
Boston Crime Analisys test.
ejaj/transaction-guard
Develop a prediction model capable of learning to detect whether a transaction is fraudulent or a genuine purchase.
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.
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
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.