surendiran-20cl/Credit_Score_Classification

Developed a multiclass classification system using supervised learning to predict credit score tiers from financial data. Applied EDA, feature engineering, hyperparameter tuning, and evaluated models using ROC-AUC, confusion matrices, and feature importance.

Language: Jupyter Notebook - Size: 1010 KB - Last synced at: 5 days ago - Pushed at: 5 days ago - Stars: 0 - Forks: 0

pytorch/captum

Model interpretability and understanding for PyTorch

Language: Python - Size: 303 MB - Last synced at: 6 days ago - Pushed at: 12 days ago - Stars: 5,174 - Forks: 513

11NOel11/chaos_nonchaos_predictor_nn

AI-powered chaos detection using Simple Harmonic Motion (SHM) & Double Pendulum examples! Compare a Neural Network (NN) with the Lyapunov exponent method to classify chaotic vs. non-chaotic systems. Features Deep Learning, SHAP explainability, F1-score, precision, recall, and stunning visualizations!

Language: Python - Size: 521 KB - Last synced at: 9 days ago - Pushed at: 9 days ago - Stars: 1 - Forks: 0

mmschlk/shapiq

Shapley Interactions and Shapley Values for Machine Learning

Language: Python - Size: 307 MB - Last synced at: 8 days ago - Pushed at: 10 days ago - Stars: 504 - Forks: 34

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.

Language: Jupyter Notebook - Size: 1.67 MB - Last synced at: 9 days ago - Pushed at: 4 months ago - Stars: 3 - Forks: 0

EthicalML/xai

XAI - An eXplainability toolbox for machine learning

Language: Python - Size: 17.8 MB - Last synced at: 14 days ago - Pushed at: over 3 years ago - Stars: 1,162 - Forks: 180

DIME-XAI/dime-xai 📦

Implementation of Dual Interpretable Model-agnostic Explanations for Rasa DIET classifiers

Language: Python - Size: 40.7 MB - Last synced at: 9 days ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0

kochlisGit/ProphitBet-Soccer-Bets-Predictor

ProphitBet is a Machine Learning Soccer Bet prediction application. It analyzes the form of teams, computes match statistics and predicts the outcomes of a match using Advanced Machine Learning (ML) methods. The supported algorithms in this application are Neural Networks, Random Forests & Ensembl Models.

Language: Python - Size: 3.47 MB - Last synced at: 9 days ago - Pushed at: 3 months ago - Stars: 389 - Forks: 132

nredell/ShapML.jl

A Julia package for interpretable machine learning with stochastic Shapley values

Language: Julia - Size: 529 KB - Last synced at: 11 days ago - Pushed at: 12 months ago - Stars: 90 - Forks: 8

RiccardoSpolaor/Verbal-Explanations-of-Spatio-Temporal-Graph-Neural-Networks-for-Traffic-Forecasting

An eXplainable AI system to elucidate short-term speed forecasts in traffic networks obtained by Spatio-Temporal Graph Neural Networks.

Language: Jupyter Notebook - Size: 118 MB - Last synced at: 8 days ago - Pushed at: about 1 year ago - Stars: 18 - Forks: 2

razamehar/Naples-Diaper-Market-Geo-Analytics-for-Potential-Estimation

Analyzing Fater company's diaper market potential and enhancing revenue estimation for Naples stores: A Socio-Demographic, Territorial, and Points of Interest Perspective

Language: Python - Size: 3.86 MB - Last synced at: 21 days ago - Pushed at: 21 days ago - Stars: 1 - Forks: 0

Yahlawat/Credit-Card-Default-Prediction

Predicting default payments using gradient boosting and ensemble machine learning models. Includes EDA, model comparison (Random Forest, XGBoost, LightGBM, etc.), ROC analysis, and feature importance on Taiwanese credit card client data.

Language: Jupyter Notebook - Size: 784 KB - Last synced at: 21 days ago - Pushed at: 21 days ago - Stars: 0 - Forks: 0

ccomkhj/interpretable-lightgbm

SHAP explainer for LightGBM models - Generate feature importance plots, dependence plots, and prediction explanations with one line of code. Make your gradient boosting models interpretable for stakeholders.

Language: Python - Size: 0 Bytes - Last synced at: 22 days ago - Pushed at: 22 days ago - Stars: 0 - Forks: 0

Pegah-Ardehkhani/Customer-Churn-Prediction-and-Analysis

Analysis and Prediction of the Customer Churn Using Machine Learning Models (Highest Accuracy) and Plotly Library

Language: Jupyter Notebook - Size: 1.99 MB - Last synced at: 18 days ago - Pushed at: over 2 years ago - Stars: 10 - Forks: 4

cassnutt/Predicting_heart_disease

A dataset containing over 70,000 data points, 12 features, and one target variable were used to analyze if machine learning could predict if an individual has cardiovascular disease.

Language: Jupyter Notebook - Size: 4.3 MB - Last synced at: 27 days ago - Pushed at: 27 days ago - Stars: 2 - Forks: 1

lhallee/featureranker

Python package for feature ranking

Language: Jupyter Notebook - Size: 2.79 MB - Last synced at: 8 days ago - Pushed at: about 1 month ago - Stars: 6 - Forks: 0

sylvaticus/BetaML.jl

Beta Machine Learning Toolkit

Language: Julia - Size: 33.3 MB - Last synced at: 7 days ago - Pushed at: 3 months ago - Stars: 98 - Forks: 13

LadaRudnitckaia/telemarketing-optimization

Develoment of a machine learning model optimizing telemarketing through prediction of marketing calls that don't lead to customer conversion

Language: Jupyter Notebook - Size: 14.6 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

sergezaugg/feature_importance

Assess procedures for "feature importance" against predictive performance

Language: Python - Size: 2.14 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 0

duxuhao/Feature-Selection

Features selector based on the self selected-algorithm, loss function and validation method

Language: Python - Size: 10 MB - Last synced at: 28 days ago - Pushed at: almost 6 years ago - Stars: 676 - Forks: 199

Edanur-Y/Laptop-Price-Prediction-with-Regression-Models

Comparing the performances of multi-layer perceptron, k-nearest neighbors, random forest, gradient boosting and extreme gradient boosting regression and on laptop data to predict the price.

Language: Jupyter Notebook - Size: 51.8 KB - Last synced at: about 1 month ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

Arsalaan-Ahmad/Diabetes-Prediction-Comparing-Random-Forest-Logistic-Regression

A machine learning project comparing Random Forest and Logistic Regression for diabetes prediction using the Pima Indians Diabetes Dataset.

Language: MATLAB - Size: 41.8 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

kartheekdama/Salary-Prediction

This salary prediction model leverages machine learning techniques, including Random Forest, Decision Tree, and Linear Regression, to estimate salaries based on individual attributes such as age, gender, education level, job title, and years of experience. The Random Forest model outperforms the others, achieving the highest R-squared score.

Language: Jupyter Notebook - Size: 881 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

carpentries-incubator/fair-explainable-ml

Fair and explainable ML workshop

Language: Jupyter Notebook - Size: 38.5 MB - Last synced at: 7 days ago - Pushed at: 7 days ago - Stars: 3 - Forks: 4

Stephen-Adwini-Badu/05.-BCG-X-Project

This project involved developing a Random Forest classifier to predict user churn. The work included plotting feature importance to identify key factors influencing churn and evaluating metrics to assess the model's performance. The insights gained from this project were used to develop strategies to improve user retention.

Language: Jupyter Notebook - Size: 2.53 MB - Last synced at: about 1 month ago - Pushed at: 2 months ago - Stars: 1 - Forks: 0

praveendecode/US_HPI_Prediction

Explore the dynamics of US home prices over two decades using a robust Random Forest Regressor model. Achieving a 99.87% R2 score, uncover key factors influencing real estate trends

Language: Jupyter Notebook - Size: 1.54 MB - Last synced at: 17 days ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

wajoel/Customer-Segmentation-in-USA

Advanced Customer Segmentation methods in R

Language: R - Size: 569 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 1 - Forks: 0

Pegah-Ardehkhani/Predictive-Maintenance-Using-ML

A machine learning project for predictive maintenance, designed to forecast equipment failures and optimize maintenance schedules to reduce downtime and operational costs

Language: Jupyter Notebook - Size: 1.04 MB - Last synced at: 6 days ago - Pushed at: 5 months ago - Stars: 4 - Forks: 0

abdullah-al-masud/msdlib

This is a custom library for data processing, visualization and machine learning tools.

Language: Python - Size: 51.5 MB - Last synced at: 15 days ago - Pushed at: 3 months ago - Stars: 13 - Forks: 2

MahirBye/KLASIFIKASI-TINGKAT-KEMISKINAN-DI-INDONESIA

Proyek Bootcamp DIBIMBING

Language: Jupyter Notebook - Size: 118 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

JamesCWeber/BCG-X-Data-Science-Project-Part-3-Churn-Prediction

The last task given to me while completing the BCG X Data Science microinternship. Create a Random Forest model using data from part 2. The model will predict which customers will churn and what features are influential to customer's decision to churn.

Language: Jupyter Notebook - Size: 5.65 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

nredell/shapFlex

An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model

Language: R - Size: 2.13 MB - Last synced at: 8 days ago - Pushed at: almost 5 years ago - Stars: 74 - Forks: 7

statmlben/dnn-inference

Significance tests of feature relevance for a black-box learner

Language: Python - Size: 568 MB - Last synced at: 8 days ago - Pushed at: 9 months ago - Stars: 18 - Forks: 4

sushant1827/Traffic-Forecasting-using-IoT-Sensor-Data

Demonstrates how to utilize XGBoost for traffic forecasting using data gathered from IoT sensors, highlighting its efficiency in processing complex datasets and delivering accurate predictions.

Language: Jupyter Notebook - Size: 908 KB - Last synced at: 9 days ago - Pushed at: 4 months ago - Stars: 4 - Forks: 0

AbbasPak/Feature-Importance-in-Machine-Learning

A comprehensive resource for understanding, implementing, and comparing various methods for feature importance in machine learning. This repository includes theoretical explanations, practical examples, and code snippets for techniques like permutation importance, SHAP, LIME, and more.

Size: 42 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

shussin245/GeneExpressionAnalysis

A tutorial demonstrating how to analyze gene expression data using elastic net models to predict patient responses to immunotherapy, focusing on regularization, cross-validation, and feature importance.

Language: Jupyter Notebook - Size: 627 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

Pegah-Ardehkhani/Flight-Price-EDA-and-Prediction

Analyze and Predict the Flight Price Using Machine Learning Models and Plotly Library

Size: 3.49 MB - Last synced at: about 2 months ago - Pushed at: over 2 years ago - Stars: 4 - Forks: 2

csinva/hierarchical-dnn-interpretations

Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)

Language: Jupyter Notebook - Size: 48.7 MB - Last synced at: 9 days ago - Pushed at: over 3 years ago - Stars: 128 - Forks: 23

kingychiu/target-permutation-importances

A Python Package that computes Target Permutation Importances (Null Importances) of a machine learning model.

Language: Python - Size: 693 KB - Last synced at: 2 days ago - Pushed at: 4 months ago - Stars: 14 - Forks: 1

sile/fanova

A Rust implementation of fANOVA (functional analysis of variance)

Language: Rust - Size: 140 KB - Last synced at: 10 days ago - Pushed at: almost 3 years ago - Stars: 15 - Forks: 1

maruti-iitm/species_area_scaling

Quantifying Dissolved Organic Matter Scaling Relationships and Trends in Watersheds

Language: Python - Size: 236 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 1 - Forks: 0

AdewoleK/Flight-Prediction-Customer-Buying-Behaviour

Analysis on predicting customer buying behavior while booking flight on British Airways

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

dominance-analysis/dominance-analysis

This package can be used for dominance analysis or Shapley Value Regression for finding relative importance of predictors on given dataset. This library can be used for key driver analysis or marginal resource allocation models.

Language: Python - Size: 4.54 MB - Last synced at: 5 months ago - Pushed at: over 1 year ago - Stars: 153 - Forks: 57

csinva/transformation-importance

Using / reproducing TRIM from the paper "Transformation Importance with Applications to Cosmology" 🌌 (ICLR Workshop 2020)

Language: Jupyter Notebook - Size: 75.6 MB - Last synced at: 21 days ago - Pushed at: over 4 years ago - Stars: 9 - Forks: 1

csinva/disentangled-attribution-curves

Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"

Language: Python - Size: 4.63 MB - Last synced at: 22 days ago - Pushed at: about 4 years ago - Stars: 27 - Forks: 4

laura-rieger/deep-explanation-penalization

Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584

Language: Jupyter Notebook - Size: 248 MB - Last synced at: 5 months ago - Pushed at: about 4 years ago - Stars: 127 - Forks: 14

AdewoleK/Credit-Card-Fraud-Prediction

Using both exploratory and machine learning techniques to identify key indicators of fraud and the regions that needed enhanced preventive measures.

Language: Jupyter Notebook - Size: 0 Bytes - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

aerdem4/lofo-importance

Leave One Feature Out Importance

Language: Python - Size: 807 KB - Last synced at: 6 months ago - Pushed at: over 1 year ago - Stars: 817 - Forks: 84

maheera421/Bulldozer-Price-Prediction-Model

Prediction of the auction prices of bulldozers using historical data.

Language: Jupyter Notebook - Size: 17.6 MB - Last synced at: about 1 month ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

maheera421/Heart-Disease-Diagnosis-Model

A machine learning project designed to predict the likelihood of heart disease based on a set of health indicators.

Language: Jupyter Notebook - Size: 1020 KB - Last synced at: 14 days ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

roye10/ShapleyLorenz

IN PROGRESS - after the paper "Shapley-Lorenz decompositions in eXplainable Artificial Intelligence" by Giudici and Raffinetti - 2020

Language: Python - Size: 429 KB - Last synced at: about 1 month ago - Pushed at: about 4 years ago - Stars: 3 - Forks: 1

mattiaferrarini/Applying-ML-to-NPS-Screening

Application of Machine Learning algorithms to the screening of New Psychoactive Substances.

Language: Jupyter Notebook - Size: 1.06 MB - Last synced at: about 1 month ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

Arfa-Ahsan/Customer-Churn-Prediction-Project

Developing a machine learning model to predict customer churn as it is essential for proactively retaining valuable customers.

Language: Jupyter Notebook - Size: 19.3 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

paulapoley/bone-marrow-transplant-analysis

Análisis predictivo de trasplante de médula ósea en pacientes pediátricos utilizando modelos de regresión logística y random forest. Incluye análisis y visualizaciones de datos clínicos para predecir la recaída post-trasplante.

Size: 1.71 MB - Last synced at: 19 days ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0

srosalino/Predictive_Modeling_for_Agriculture

Sowing Success: How Machine Learning Helps Farmers Select the Best Crops

Language: Jupyter Notebook - Size: 273 KB - Last synced at: about 2 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0

AliAmini93/Telecom-Churn-Analysis

Developed a churn prediction model using XGBoost, with comprehensive data preprocessing and hyperparameter tuning. Applied SHAP for feature importance analysis, leading to actionable business insights for targeted customer retention.

Language: Jupyter Notebook - Size: 2.52 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 7 - Forks: 0

nitin6753/Customer_Satisfaction_Prediction

The airline is interested in predicting whether a future customer would be satisfied with their services given previous customer feedback about their flight experience. A decision tree was modelled to predict whether or not a customer will be satisfied with their flight experience.

Language: Jupyter Notebook - Size: 17.2 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0

zahraatashgahi/Neuron-Attribution

[ECAI 2024] Unveiling the Power of Sparse Neural Networks for Feature Selection

Language: Python - Size: 594 KB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0

mattiacarletti/DIFFI

Official repository of the paper "Interpretable Anomaly Detection with DIFFI: Depth-based Isolation Forest Feature Importance", M. Carletti, M. Terzi, G. A. Susto.

Language: Jupyter Notebook - Size: 1.33 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 25 - Forks: 9

mokeddembillel/Student-Performance-Prediction

Using Machine learning to predict a student final grade

Language: Python - Size: 113 KB - Last synced at: about 1 month ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0

kyaiooiayk/Feature-Correlation-Selection-Importance-Engineering-Notes

Notes, tutorials, code snippets and templates focused on Features Correlation | Selection | Importance | Engineering for Machine Learning

Language: Jupyter Notebook - Size: 6.05 MB - Last synced at: 5 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0

BhadraNivedita/How-to-calculate-feature-importance-in-Python

Compute feature importance in machine learning model

Language: Jupyter Notebook - Size: 37.1 KB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 1

sahilmate/ebm-breast-cancer-classifier

This repository implements an Explainable Boosting Machine (EBM) model for breast cancer classification using scikit-learn and interpret. The project includes data preprocessing, model training, accuracy evaluation, and feature importance visualization.

Language: Jupyter Notebook - Size: 315 KB - Last synced at: about 2 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0

afairless/binary_classification_shap

Run histogram-based gradient boosted trees binary classifier on generated data and interpret results with standard metrics, SHAP, and supervised clustering

Language: Python - Size: 22.5 KB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0

S84v/oil-and-gas-prediction

This project provides a thorough analysis of the crude oil production data from the Volve field, offering valuable insights into production trends and future forecasts.

Language: Jupyter Notebook - Size: 9.51 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0

Bodegraven1991/Kickstarter_machine_learning_project

Second project for Data Science Bootcamp at neuefische. Perform EDA, data cleaning and machine learning modelling with kickstarter dataset the was provided

Language: Jupyter Notebook - Size: 65.1 MB - Last synced at: 10 months ago - Pushed at: 10 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

juliorodrigues07/url_detection

Malicious URL detector built with deep exploration on feature engineering.

Language: Python - Size: 144 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 1 - Forks: 0

connect-web/OSRS-Notebooks

Visualizing features & data for ML using Random Forests, NLP & graphs for PCA analysis.

Language: Jupyter Notebook - Size: 1.09 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

Eakta08/Breast-Cancer-Prediction

This a Deep Learning and Machine Learning project performed on Wisconsin Breast Cancer dataset.

Language: Jupyter Notebook - Size: 4.43 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

snchimata/Airbnb-Boston-Data-Analysis

Language: Jupyter Notebook - Size: 45.6 MB - Last synced at: 11 months ago - Pushed at: over 5 years ago - Stars: 0 - Forks: 0

filipbagen/golf-performance-analysis

⛳️ This project, within the course Sports Analytics, TDDE64, at Linköping University, uses Random Forest and SVM models to predict tournament outcomes, revealing insights into the factors that drive player success in golf.

Language: Jupyter Notebook - Size: 2.58 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

tedoaba/House-Price-Prediction-App

House-Price-Prediction-App

Language: Python - Size: 710 KB - Last synced at: about 1 month ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 0

Chaymae-ipynb/Machine-Learning-projects

Language: Jupyter Notebook - Size: 1.08 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

Faridghr/WirelessChurnPrediction

The repository contains comprehensive assessment reports and Jupyter Notebook files aimed at addressing key questions related to predicting wireless churn and identifying the features driving churn.

Language: Jupyter Notebook - Size: 1.14 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 0 - Forks: 0

Ninad077/Machine_Learning-Decision_Tree

Content: Root node, Decision node & Leaf nodes, Attribute Selection Measure (ASM), Feature Importance (Information Gain), Gini index

Language: Jupyter Notebook - Size: 356 KB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 0 - Forks: 0

halepino/WorkplaceCulture_DataMining

ML modeling and feature importance analysis conducted to identify/inform company practices related work interference due to mental health.

Language: Jupyter Notebook - Size: 2.73 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 0 - Forks: 0

dgluesen/relevance-nfl-statistics

Nowadays, sports events live above all from their media coverage, which includes cheering up winners and writing down losers. Statitstics are used to underpin the own argumentation in this reports. But is there any cherry picking here? Are only those statistics used that make the report/commentary look completely logical? In order to give an initial assessment of the relevance of typically used statistics of NFL games, a simple but easily understandable machine learning approach is presented. This reveal statistics which might be used as a solid basis for argumentation.

Language: Jupyter Notebook - Size: 3.58 MB - Last synced at: about 1 year ago - Pushed at: over 5 years ago - Stars: 1 - Forks: 0

Lefteris-Souflas/Modern-Slavery-Analysis

Jupyter notebook using machine learning techniques to explore the complex drivers of modern slavery. Models from a research paper are replicated and evaluated . Actions also include filling missing data, training regression models, and analyzing feature importance.

Language: Jupyter Notebook - Size: 4.08 MB - Last synced at: about 2 months ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

Kebab-kun/Sector-based-Time-Series-Classification-and-Similarity-Analysis

Sector based classification with feature engineering and tsfresh. Looking 3 months momentum of stocks.

Language: Jupyter Notebook - Size: 1.66 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

sushant1827/Finding-Donors-for-Charity-using-Machine-Learning

Machine Learning Nano-degree Project : To help a charity organization identify people most likely to donate to their cause

Language: Jupyter Notebook - Size: 792 KB - Last synced at: 15 days ago - Pushed at: over 5 years ago - Stars: 1 - Forks: 1

srimallipudi/House-Price-Prediction-Using-Decision-Tree-ML-Algorithm

This repository contains a Decision Tree Regression model developed to predict house sale prices based on various predictor variables, aiming to provide accurate predictions and insights into regional differences in real estate values.

Language: Python - Size: 1.66 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

unnir/CancelOut

CancelOut is a special layer for deep neural networks that can help identify a subset of relevant input features for streaming or static data.

Language: Jupyter Notebook - Size: 213 KB - Last synced at: about 1 year ago - Pushed at: over 4 years ago - Stars: 26 - Forks: 13

JonathanCrabbe/CARs

This repository contains the implementation of Concept Activation Regions, a new framework to explain deep neural networks with human concepts. For more details, please read our NeurIPS 2022 paper: 'Concept Activation Regions: a Generalized Framework for Concept-Based Explanations.

Language: Python - Size: 2.86 MB - Last synced at: 11 months ago - Pushed at: over 2 years ago - Stars: 9 - Forks: 2

portfolioRM/Chicago-Community-Areas

An exploratory analysis of Chicago community areas

Language: R - Size: 589 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

israelh88/Capstone-Google_Advanced_Data_Analytics

Capstone for Google Advanced Data Analytics Professional Certificate

Size: 559 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

chunwangpro/textual-information-extraction-and-numeric-processing

Extract textual information from Amazon products reviews and draw correlations through regression and fluctuation analysis.

Language: Jupyter Notebook - Size: 29.9 MB - Last synced at: about 1 year ago - Pushed at: about 5 years ago - Stars: 6 - Forks: 3

michaeljneely/sparse-attention-explanation

Analysis of 'Attention is not Explanation' performed for the University of Amsterdam's Fairness, Accountability, Confidentiality and Transparency in AI Course Assignment, January 2020

Language: Python - Size: 48.3 MB - Last synced at: about 1 year ago - Pushed at: about 5 years ago - Stars: 4 - Forks: 0

janasatvika/Optimizing-Classification-Models-using-Permutation-Feature-Importance-Method

High data dimensionality and irrelevant features can negatively impact the performance of machine learning algorithms. This repository implements the Permutation feature importance method to enhance the performance of some machine learning models by identifying the contribution of each feature used.

Language: Jupyter Notebook - Size: 1.99 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

juliorodrigues07/ny_rent_pricing 📦

Rent pricing prediction on NY properties with interactive dashboards.

Language: Jupyter Notebook - Size: 13.9 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

pouyasattari/London-Bike-Sharing-Statistical-Data-Analysis-in-R

In this project, I tried to predict the number of bicycles that can be rented every hour of the day.

Language: RMarkdown - Size: 19.6 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

Mejdik/mapspades

Set of Jupyter notebooks and geospatial data developed by the MAPSPADES project to study desertification in the Algerian steppe using EO data.

Language: Jupyter Notebook - Size: 53 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

shinho123/K-Artificial-Intelligence-Electronic-Manufacturing-Data-Analysis-Competition-melting-process-

2022년 2학기 전자제조데이터분석 : 용해공정 데이터 분석 및 모델 구축(k-인공지능 제조데이터 분석 경진대회)

Language: Jupyter Notebook - Size: 691 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

vicaaa12/advanced-machine-learning

Advanced Machine Learning

Language: Jupyter Notebook - Size: 1.93 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

yujansaya/credit_risk_model

Create a model to predict which clients are more likely to default on their loans.

Language: Jupyter Notebook - Size: 14.6 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

JonathanCrabbe/Simplex

This repository contains the implementation of SimplEx, a method to explain the latent representations of black-box models with the help of a corpus of examples. For more details, please read our NeurIPS 2021 paper: 'Explaining Latent Representations with a Corpus of Examples'.

Language: Python - Size: 1010 KB - Last synced at: 11 months ago - Pushed at: about 2 years ago - Stars: 22 - Forks: 8

Broundal/Pytolemaic

Toolbox for analysis of model's quality and model's description. For further details see

Language: Python - Size: 1.16 MB - Last synced at: about 1 month ago - Pushed at: 12 months ago - Stars: 11 - Forks: 3

Aysenuryilmazz/HR_Analytics_EDA

Exploratory Data Analysis for HR dataset

Language: Jupyter Notebook - Size: 1.21 MB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

marfappv/ML-dissertation

This repository is a partial fulfilment of the requirements for the module of MSIN0114: Business Analytics Consulting Project/Dissertation for UCL School of Management.

Language: Jupyter Notebook - Size: 38.7 MB - Last synced at: over 1 year ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

CN-TU/adversarial-recurrent-ids Fork of muxamilian/privacy-tuw

Contact: Alexander Hartl, Maximilian Bachl, Fares Meghdouri. Explainability methods and Adversarial Robustness metrics for RNNs for Intrusion Detection Systems. Also contains code for "SparseIDS: Learning Packet Sampling with Reinforcement Learning" (branch "rl").

Language: TeX - Size: 2.07 GB - Last synced at: about 1 year ago - Pushed at: about 4 years ago - Stars: 14 - Forks: 11