pajaskowiak/clusterConfusion

Clustering validation with ROC Curves

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sushant1827/Machine-Learning-for-Predictive-Maintenance

Demonstrate the application of machine learning on a real-world predictive maintenance dataset, using measurements from actual industrial equipment.

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labrijisaad/Twitter-Sentiment-Analysis-with-Python

I aim in this project to analyze the sentiment of tweets provided from the Sentiment140 dataset by developing a machine learning sentiment analysis model involving the use of classifiers. The performance of these classifiers is then evaluated using accuracy and F1 scores.

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VivekSagarSingh/Probability-of-Credit-card-Default

Classification problem using multiple ML Algorithms

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sushant1827/Credit-Card-Fraud-Detection

Demonstrates the use of ML for Anomaly Detection for Credit Card Transactions: Identifying Fraudulent Activity using Imbalanced Data

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Ansuman21/Evaluating_and_Optimizing_Model_Performance_for_Business_Decision-Making

Data Science Project (Understanding Classification Model Performance Metrics M5)

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djdhairya/Brain-Stroke-Prediction

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yashmittalz/IMDB-Sentiment-Analysis

This project is a Natural Language Processing (NLP) initiative that performs sentiment analysis on IMDB movie reviews.

Language: Python - Size: 12.7 MB - Last synced at: 15 days ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

varmatilak22/Credit_Score_Prediction

This project predicts credit scores ('Good', 'Standard', 'Poor') using a streamlined ML pipeline. It includes data extraction, cleaning, and preprocessing. Key techniques are Mutual Information for feature selection, PCA for dimensionality reduction, and XGBoost for accurate and efficient model training, ensuring reliable and robust predictions.

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aarryasutar/Logistic_Regression_on_Age_Prediction

This code evaluates the performance of a logistic regression model on age prediction using various features to predict a binary target variable, calculating metrics to determine the performance. It evaluates the comparison, identifies favorable features, and visualizes the ROC-AUC curve to determine the best model performance.

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larenwell/ai-ml-rfe-optuna-ferreyros-challenge

At ferreyros, prioritizing sales opportunities for spare parts and services allows them to provide the best service to customers who need it most. This challenge is to use historical opportunity data to estimate the probability of closing new opportunities.

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Niteshchawla/OLA-EnsembleLearning

Recruiting and retaining drivers is seen by industry watchers as a tough battle for Ola. Churn among drivers is high and it’s very easy for drivers to stop working for the service on the fly or jump to Uber depending on the rates.

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Niteshchawla/LoanTap-LogisticRegression

Given a set of attributes for an Individual, determine if a credit line should be extended to them. If so, what should the repayment terms be in business recommendations?

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ChaitanyaK77/Heart-Disease-prediction-with-Advanced-SMOTE-Implementation-and-ROC-learning

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harmanveer-2546/Wafer-Fault-Detection

The goal is to eliminate manual work in identifying faulty wafers. Opening and handling suspected wafers disrupts the entire process. False negatives result in wasted time, manpower, and costs.

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edwinthomas444/machine-learning

e2e machine learning pipeline using a config based approach for classification problems. Supports grouping and grading classifiers in addition to online learning algorithms

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pajaskowiak/aucc

AUCC (Python Implementation)

Language: Python - Size: 9.77 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 1

xavierfactor/Diabetes-Predictive-Analytics

ML models that predict diabetic status

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minyansh7/CustomerSegmentationPredictionforArvato

Build Customer Segments and predict customer responses to marketing campaign for Arvato Financial Services

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venkatesh-eranti/classification_milestone_project

Predicting Heart Disease using Machine Learning

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domingosdeeulariadumba/Penguins_Classification

Multiclass classification model of penguins species.

Language: Python - Size: 380 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

GunturWibawa/SentimentAnalysisJU

Junky Union is creating a system to sort movie reviews. They aim to train a model to detect negative reviews using the IMBD dataset with polarity labeling. The model must classify reviews as positive or negative with an F1 score of at least 0.85.

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agomolka/KaggleTitanicCompetition

Predict survival on the Titanic and get familiar with ML basics.

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Tejas-TA/Transformer-BERT-SMS-Spam-Detection

Spam SMS Detection Project implemented using NLP & Transformers. DistilBERT - a hugging face Transformer model for text classification is used to fine-tune to best suit data to achieve the best results. Multinomial Naive Bayes achieved an F1 score of 0.94, the model was deployed on the Flask server. Application deployed in Google Cloud Platform

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karansondh/bee-classifictaion

Classifier that predicts bee species from images. We have used Support Vector Machine(SVM) model. It can predict different bee species with an accuracy of 68%.

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jianninapinto/Default-Loan-Predictor

Trained a classifier by using labeled data and SMOTE techniques to predict if a borrower will default on a loan. The machine learning model is intended to be used as a reference tool to help investors make informed decisions about lending to potential borrowers based on their ability to repay. The purpose is to lower risk and maximize profit.

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Harmanveer2546/Heart

Predicting the presence of heart disease based on several health-related factors and Performing - i.) Data Cleaning ii.) Data Pre-Processing iii.) EDA iv.) Compare 5 different classification algorithms (Logistic Regression, Decision Tree, Random Forest, KNN and SVC)

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chomiczdawid/simple-credit-scoring

PD model using Logistic Regression in Python

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varshith-alladi/Cancer-Classification-Based-On-Gene-Expression-Data

This is a Bio Informatics project for the classification of types of Leukemia Cancer i.e., ALL & AML based on gene expression data. An accuracy of 0.94 has been achieved by using Support Vector Machine(SVM). The dataset has been collected from 'Kaggle' where gene descriptions are given as the features.

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JitalEn/LeadScore

Lead scoring case study

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shanuhalli/Assignment-Neural-Networks

Predict the Burned Area of Forest Fire with Neural Networks and Predicting Turbine Energy Yield (TEY) using Ambient Variables as Features.

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jaunel/ML-Classification--Customer-Churn-Prediction

Developed Machine Learning Model to categorize customer with more than 91% accuracy and 88% roc_auc score. Best ML model is selected after evaluating all performance metric like Accuracy, Precision & recall

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AdityaBrahme98/Fraud_detection_ML

Use various machine learning models to see how accurate they are in detecting whether a transaction is a normal payment or a fraud.

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Buffless24/BreastCancer-Analysis-and-Prediction

Data analysis, visualization and prediction to predict whether a patient has benign or malignant breast cancer based on properties of the cancer

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Kovenda/R-Shiny-App-to-predict-Factors-Affecting-Survival-of-CHD

R Shiny App to determine the factors that are most influential in patients’ survival of CHD. I created a Logistic Regression model in R using RStudio to predict the survival of CHD patients. Retrieved the data from the PHIS database using SQL & built tableau dashboards. The model predicted the survival of CHD with an AUC of over .90 and indicated that a higher EF % is a major factor.

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SurajKumarMondal/Santander-Customer-Satisfaction

In this project, we have worked with hundreds of anonymized features to predict if a customer is satisfied or dissatisfied with their banking experience.

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rochitasundar/Classification-booking-cancelation-prediction-StarHotels

The aim is to develop an ML- based predictive classification model (logistic regression & decision trees) to predict which hotel booking is likely to be canceled. This is done by analysing different attributes of customer's booking details. Being able to predict accurately in advance if a booking is likely to be canceled will help formulate profitable policies for cancelations & refunds.

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SurayaSumona/Telecom_Customer_Churn_Prediction

Machine Learning with Python

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SurayaSumona/Heart_Disease_Prediction_Analysis

Machine Learning with Python

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LTW85/skflex

Flexible utility functions for use with the sklearn library

Language: Python - Size: 295 KB - Last synced at: 26 days ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0

TonmoyTalukder/Churning-Telecom-Company-Prediction

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SmartNamDevoloper/Logistic_Regression

This is a project demonstrating Logistic Regression method using Python. An education company named X Education sells online courses to industry professionals. On any given day, many professionals who are interested in the courses land on their website and browse for courses.

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SmartNamDevoloper/Telecom_Customer_churn_Classification

This project demonstrates building a classification model for imbalanced data. Feature engineering, feature selection and extensive EDA. Comparing of logistic regression, random forest and ADA Boost models are done before finalizing the best model.

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ridwan102/NJNY_Flight_Delay

Presentation Link: https://www.youtube.com/watch?v=MNy65IYIx24&t=13s

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