SVM, Logistic Regression, K-Nearest Neighbors Classifier, GaussianNB, Random Forest, XGBoost, DecisionTree Classifier, Ensembled Classifier, ExtraTrees Classifier, Voting Classifier
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Updated
Oct 3, 2020 - Jupyter Notebook
SVM, Logistic Regression, K-Nearest Neighbors Classifier, GaussianNB, Random Forest, XGBoost, DecisionTree Classifier, Ensembled Classifier, ExtraTrees Classifier, Voting Classifier
In this project, Naive Bayes and Logistic Regression models are used to develop a text classification system for Turkish news articles.
Naive Bayes (From Scratch)
Heart disease describes a range of conditions that affect your heart. Diseases under the heart disease umbrella include blood vessel diseases, such as coronary artery disease, heart rhythm problems (arrhythmia), and heart defects you’re born with (congenital heart defects), among others.
Predicting house prices can help determine the selling price of a house in a particular region and can help people find the right time to buy a home.
A Flask web app which predicts whether it will rain tomorrow or not.
Heart disease describes a range of conditions that affect your heart. Diseases under the heart disease umbrella include blood vessel diseases, such as coronary artery disease, heart rhythm problems (arrhythmia), and heart defects you’re born with (congenital heart defects), among others.
Analysis of SMS tagged 5K+ messages collection to classify them as spam or ham. Used Natural Language Processing techniques to transform data into an understandable format.
Predicts the qualified employee for promotion using Classification
This project is done during the data science T5 bootcamp. Using HR dataset and applying machine learning classification algorithms to predict eligible employees for promotions. Hence save time and effort and expedite the process of promotions in the company.
Classifying iris flower dataset by using Naive Bayes classifier
classifying employee attrition
‘Buy Now, Pay Later’ (BNPL) is a type of short-term financing used by start-ups like Slice, ZestMoney, Simpl, LazyPay, and Uni, are lowering the bars while approving applications. Building models to detect such customers beforehand.
Expresso Churn Prediction Challenge - dealing with imbalanced dataset
This repository contains introductory notebooks for Naive bayes algorithm
Final practical work of the Machine Learning Course with Python dictated by the UTN.
Performance Comparison of Three Classifiers for the Classification of Breast Cancer Dataset
The aim is to create a classifier that indicates whether a requested transaction is genuine or fraudulent.
🧠 DMAD - Differential Morphing Attack Detection. A project for Fundamentals of Computer Vision and Biometrics course at the University of Salerno.
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