archd3sai/Customer-Survival-Analysis-and-Churn-Prediction

In this project, I have utilized survival analysis models to see how the likelihood of the customer churn changes over time and to calculate customer LTV. I have also implemented the Random Forest model to predict if a customer is going to churn and deployed a model using the flask web app.

Language: Jupyter Notebook - Size: 40.2 MB - Last synced at: 13 days ago - Pushed at: over 2 years ago - Stars: 197 - Forks: 72

Kamal-Shirupa/Solar-Power-Forecasting

This project predicts solar panel energy output based on weather conditions and irradiance levels using a hybrid model of Gradient Boosting and LSTM .

Size: 649 KB - Last synced at: 13 days ago - Pushed at: 22 days ago - Stars: 1 - Forks: 0

Nirmala-research/YOLOv7-XAI

Multiclass Skin lesion localization and Detection with YOLOv7-XAI Framework with explainable AI

Language: Python - Size: 1.59 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 1 - Forks: 0

oegedijk/explainingtitanic

A demonstration of the explainerdashboard package that that displays model quality, permutation importances, SHAP values and interactions, and individual trees for sklearn RandomForestClassifiers, etc

Language: Python - Size: 71.9 MB - Last synced at: 9 days ago - Pushed at: 6 months ago - Stars: 19 - Forks: 7

Pranav2092/Intrustion-Detection-Using-Modified-Tree-SHAP

Language: Jupyter Notebook - Size: 118 KB - Last synced at: 16 days ago - Pushed at: 5 months ago - Stars: 1 - Forks: 0

oegedijk/explainerdashboard

Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

Language: Python - Size: 80.2 MB - Last synced at: 6 months ago - Pushed at: 9 months ago - Stars: 2,303 - Forks: 332

LGDiMaggio/Explainable-AI-for-Machine-Fault-Diagnosis

This project uses Explainable AI (XAI) to interpret machine learning models for diagnosing faults in industrial bearings. By applying SVM and kNN models and leveraging SHAP values, it enhances the transparency and reliability of machine learning in industrial condition monitoring.

Language: Jupyter Notebook - Size: 5 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

victor-malheiro/Banco-de-Portugal-classification-about-companies-being-late-in-reporting-tasks

Classification model using Gradient Goosted Trees with feature selection and explainability

Size: 1.08 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0

rdemarqui/financial_distress_prediction

Financial distress prediction from Kaggle

Language: Jupyter Notebook - Size: 15.8 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0

haghish/shapley

Weighted Shapley Values and Weighted Confidence Intervals for Multiple Machine Learning Models and Stacked Ensembles

Language: R - Size: 2.88 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 10 - Forks: 0

Scrayil/Heart_Failure_Prediction

This project aims to predict heart failure outcomes by applying statistical learning algorithms. The goal is to improve the prediction accuracy through the SuperLearner algorithm.

Language: R - Size: 12.2 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

Arsu-Lab/Different-Algorithms-Uncover-Different-Patterns-BrainAge-Prediction

Github Repository for the paper "Different Algorithms (Might) Uncover Different Patterns: A Brain-Age Prediction Case Study" - BIBM 2023

Language: Jupyter Notebook - Size: 68.5 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 4 - Forks: 0

anikdas2204/XAI-Heart-Attack

XAI analytics to understand the working of SHAP values

Language: Jupyter Notebook - Size: 241 KB - Last synced at: about 1 year ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0

tendyzen/tendyzen.github.io

Repo for Manzano Analytics HTML website

Language: HTML - Size: 44.5 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

boldirev-as/Digital_perm23

ML-solution of the case of the District hackathon Leaders of Digital 2023. The task was to predict accidents (accidents, pipe ruptures, fires) based on the weather forecast for each of the urban districts. Gradient boosting (macro f1), cross-validation, shap values.

Language: Jupyter Notebook - Size: 553 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

piotr-druzdzel/Explainable-AI-with-SHAP-values

Experimenting with SHAP values to explain how a given Machine Learning model works.

Language: Jupyter Notebook - Size: 404 KB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

nkarasovd/HSE_Recommender_Systems

:honeybee: Materials and homework assignments for HSE recommender systems course

Language: Jupyter Notebook - Size: 5.99 MB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0

lucasthim/covid19-prediction

Prediction if patients with symptoms have COVID-19 based on clinical variables (blood related variables, urine related variables, age, etc)

Language: Jupyter Notebook - Size: 22.2 MB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0

zhousrhhh/Loan-Default-Prediction

Loan-Default-Prediction

Language: Jupyter Notebook - Size: 3.79 MB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

bhroben/Feature-importance-methods-of-simulated-binary-black-holes

This project was developed during the course Laboratory of Computational Physics

Language: Jupyter Notebook - Size: 0 Bytes - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

CSFelix/Data-Science-Mental-Maps

🐍 Mental Maps Related to Contents in Data Science 🐍

Size: 51.8 KB - Last synced at: 22 days ago - Pushed at: over 2 years ago - Stars: 7 - Forks: 0

risto-trajanov/explainable-landscape-aware-performance-regression

Explainable Landscape-Aware Optimization Performance Prediction

Language: Jupyter Notebook - Size: 1.88 GB - Last synced at: 8 days ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 1

adiag321/CRM-Analysis-for-Marketing-data

In this project, we have to create a predictive model which allows the company to maximize the profit of the next marketing campaign

Language: Jupyter Notebook - Size: 8.67 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 4 - Forks: 0

bernatsort/Barcelona_house_price_prediction

Predicción del precio de venta de las viviendas en venta y de las viviendas en alquiler de Barcelona.

Language: Jupyter Notebook - Size: 27.5 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

sachin17git/Malware-detection-ML

Android malware detection using machine learning.

Language: Jupyter Notebook - Size: 8.81 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

KerryDRX/Bank-Customer-Churn-Prediction

Bank customer churn prediction using supervised learning models.

Language: Jupyter Notebook - Size: 206 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

dikaaka/In-Vehicle-Coupon-Recommendation-Project

Generate predictive model using supervised learning method to enhanced coupon acceptance rate using python.

Language: Jupyter Notebook - Size: 6.42 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 3

kochlisGit/Wine-Preference-Analysis

The purpose of this work is the modeling of the wine preferences by physicochemical properties. Such model is useful to support the oenologist wine tasting evaluations, improve and speed-up the wine production. A Neural Network was trained using Tensorflow, which was later tuned in order to achieve high-accuracy quality predictions.

Language: Jupyter Notebook - Size: 2.77 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0

anikdas2204/XAI-Breast-Cancer-Project

XAI analytics to understand the working of SHAP values and applying it to the breast cancer dataset to get the explanation behind the predictions made.

Language: Jupyter Notebook - Size: 1.39 MB - Last synced at: about 1 year ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0

sanketsanap5/Bank-Loan-Status-Predictive-Analysis

erformed a predictive analysis on the customer's Bank Loan Application data to predict loan status. Using python, pandas, scipy, seaborn, AutoML libraries, and machine learning techniques. Used Machine Learning techniques to accurately predict the evaluation scheme if the particular loan will be 'Fully Paid' or 'Charged Off'. This means if Bank accepts a particular person's loan application will it be 'Fully Paid' or 'Charged Off'

Language: Jupyter Notebook - Size: 19 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0

saminens/Women-in-Data-Science-2020

WiDS Datathon 2020 on patient health through data from MIT’s GOSSIS (Global Open Source Severity of Illness Score) initiative.

Language: Jupyter Notebook - Size: 929 KB - Last synced at: about 2 years ago - Pushed at: about 5 years ago - Stars: 2 - Forks: 1