logisticregression

the-mrinal/ML-Notebook

Karma of Humans is AI

mdaiyub/Diabetes-Prediction

Diabetes mellitus, commonly known as diabetes is a metabolic disease that causes high blood sugar. The hormone insulin moves sugar from the blood into your cells to be stored or used for energy. With diabetes, your body either doesn’t make enough insulin or can’t effectively use its insulin.

Melanee-Melanee/NLP-Project

Natural language processing on tweets

kanwartaimoor/Classification

Multi class and Binary Classification through Logistic Regression and SVM

kunal-mallick/Water-Quality

The Water Quality Checker uses machine learning to analyze water quality parameters such as pH, solids, and conductivity, to determine if water is safe to drink. By inputting the values into the form, the model can predict if the water is fit for consumption or not.

KarthikMurugadoss1804/Prediction-of-customer-churn

In this project I intend to predict customer churn on bank data.

mb16biswas/fullstack_heart_discease_prediction_app

It is a full stack ml app , compared multiple ml models(KNeighborsClassifier, LogisticRegression, RandomForestClassifier ) , later deploy the best model using flask , and the frontend is created with react.js

prabormukherjee/ML_visualizer

Machine learning model Visualizer in web using streamlit

seb-in/10-Classifiers-Confusion-Matrix-and-Accuracy

SVM, Logistic Regression, K-Nearest Neighbors Classifier, GaussianNB, Random Forest, XGBoost, DecisionTree Classifier, Ensembled Classifier, ExtraTrees Classifier, Voting Classifier

AhmedWageh97/Machine-Learning-Projects

This repository contains some machine learning projects as a practise on machine learning course on Coursera for Prof. Andrew Ng from Stanford University.

anshkumar2311/AI-Powered-Churn-Prediction

An AI-powered dashboard to predict customer churn, visualize key factors, and help businesses reduce losses by retaining at-risk users.

denistanjingyu/IBM-HR-Analytics

Leverage external data and non-traditional methods to accurately assess and shortlist candidates with the relevant skillsets, experience and psycho-emotional traits, and match them with relevant job openings to drive operational efficiency and improve accuracy in the matching process

fidaear/detect-DDOS-using-Machine-Learning

heeh/legal_advice

Legal Taxonomy (https://taxonomy.legal/) Classifier on Reddit /r/legaladvice

ibodumas/logistic_regression

This project involves the implementation of efficient and effective Logistic Regression (FROM SCRATCH) classifiers on MNIST data set. The MNIST data comprises of digital images of several digits ranging from 0 to 9. Each image is 28 x 28 pixels. Thus, the data set has 10 levels of classes.

munir-bd/Supervised_Learning_Regression_Customer_Churn_Prediction

Context: Customer behavior prediction to retain customers

Safaa-p/Telecommunication-churn-prediction

Predicting the churn of telecommunication custumers

SevdanurGENC/Machine-Learning-Lecture-Notes

Machine Learning Lecture Notes

SuperYanka/imdb-sentiment-analysis-nlp

Sentiment analysis of IMDB movie reviews using TF-IDF and Word2Vec embeddings. Compared Logistic Regression, Naive Bayes and Random Forest models. /// Анализ обзоров фильмов на IMDB с использованием векторных представлений TF-IDF и Word2Vec. Сравнение моделей логистической регрессии, наивного байесовского алгоритма и случайного леса.

272006Sakshi/Machine-Learning-Projects

A collection of essential machine learning algorithms implemented from scratch and with libraries. Ideal for students and beginners to understand core ML concepts through hands-on examples.

5hraddha/interconnect

Interconnect : Clients Churn Prediction using ML

5hraddha/sentiment-analysis

An innovative system for filtering and categorizing movie reviews

AchrafSL/Predictive-Modeling-for-Agriculture-DataCamp

A machine learning project that helps farmers choose the best crop based on soil metrics (N, P, K, pH). This project identifies Potassium (K) as the single most predictive soil feature for crop selection, providing a cost-effective strategy for resource-limited farmers. Built with Python, scikit-lear

Ali-jalil88/-Bank-Marketing-Machine-Learning

Bank Marketing Classifcation machine learning using 6 Models each of models given another accuracy

AUX-441/Language-Detector-Model

Language Detector Loads and cleans text data, trains a language classification model using TF-IDF and Logistic Regression, evaluates it, and enables interactive language prediction with saved model reuse.

codekush123/Fake_News_Detector

A machine learning–powered tool that classifies news articles as real or fake based on their content. This project uses basic machine learning techniques to clean and vectorize text, combined with supervised learning models to detect misinformation.

farshad257/Regrassion_Income_Forcasting

A powerful stacked ensemble model for income prediction, combining GradientBoosting, AdaBoost, Bagging, Linear Regression, and Decision Trees. Achieves an impressive R² of 0.8761 on the RoS_sample_submission dataset.

JustinBenito/MathsandMachines

Machine learning Algorithms but the implementations done by me and no external libraries used

LohChiaHeung/Diabetes-Prediction-Using-Logistic-Regression

A machine learning project for diabetes prediction using Logistic Regression, SVM, and Random Forest. After model tuning, Random Forest achieved the best performance with 78.8% accuracy and 86.0% ROC-AUC, improving early diabetes detection.

mahursh/DiabetesPrediction

RimTouny/User-Forest-Cover-Type-Prediction

Predicting Colorado forest cover types using diverse ML models for classification. Baseline creation, feature selection, comparison, and tuning optimize accuracy in this University of Ottawa Master's Machine Learning course final project (2023).

samira-yousefzadeh/Parkinson-s-Disease-Detection

Machine learning project for early detection of Parkinson’s disease using voice data. Includes preprocessing, feature selection, model training, and evaluation using classifiers like Logistic Regression, KNN, Decision Tree, Random Forest, and AdaBoost. Focused on non-invasive, accurate diagnosis support.

siw2009/Sabermetrics_research

충남과학고 인포매티카 1학년들의 세이버매트릭스 & 로지스틱회귀 생구현

SURESHBEEKHANI/Maximizing-Agricultural-Yield

Unlock the potential of agricultural production with innovative optimization techniques. Explore strategies, technologies, and practices to enhance crop yields, improve efficiency, and sustainably increase output. Revolutionize farming practices and cultivate a thriving agricultural ecosystem

Uni-Creator/Lung_Cancer_Prediction

This project predicts lung cancer risks using machine learning models like Random Forest, Logistic Regression, and SVM. It analyzes patient data with features such as age, smoking habits, and symptoms. Data preprocessing, visualization, and performance evaluation ensure accurate predictions for early diagnosis.