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

cankobanz/machine-learning-projects

Machine learning course projects are contributed.

Language: Jupyter Notebook - Size: 7.85 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

SeyedMuhammadHosseinMousavi/eXplainableAI-XAI-Basics-Python

eXplainable Artificial Intelligence (XAI) Basic Algorithms on Iris Dataset

Language: Python - Size: 396 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

Eakta08/Employee-Attrition-Prediction-

This is a project based on the Employee Attrition analysis and then predicting it. Also analysing what are the major factors for attrition.

Language: Jupyter Notebook - Size: 1.15 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

ashishrana1501/Feature-Selection-and-Feature-Imporatnace

This Particular repository contains different types of Feature Selection technique.

Language: Jupyter Notebook - Size: 812 KB - Last synced at: over 1 year ago - Pushed at: almost 3 years ago - Stars: 1 - Forks: 0

CederGroupHub/s4

Solid-state synthesis science analyzer. Thermo, features, ML, and more.

Language: Jupyter Notebook - Size: 91.5 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 17 - Forks: 5

Mehrab-Kalantari/Book-Price-Prediction

Book price dataset analysis and modeling

Language: Jupyter Notebook - Size: 1.71 MB - Last synced at: 2 months ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

StarrySkyrs/Spotify_Popularity_Prediction

Built an ensemble model on the Spotify dataset to determine the popularity of songs and study feature importance using SHAP.

Language: Jupyter Notebook - Size: 15.4 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

teyang-lau/HDB_Resale_Prices

Predicted and identified the drivers of Singapore HDB resale prices (2015-2019) with 0.96 Rsquare & $20,000 MAE. Web app deployment using Streamlit for user price prediction.

Language: Python - Size: 110 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 18 - Forks: 9

tlatkowski/tf-feature-selection

Implementation of various feature selection methods using TensorFlow library.

Language: Python - Size: 33.2 KB - Last synced at: about 1 month ago - Pushed at: over 2 years ago - Stars: 9 - Forks: 3

isarn/isarn-sketches-spark

Routines and data structures for using isarn-sketches idiomatically in Apache Spark

Language: Scala - Size: 1.33 MB - Last synced at: about 1 month ago - Pushed at: 12 months ago - Stars: 29 - Forks: 12

farrellwahyudi/Predicting-Ad-Clicks-Classification-by-Using-Machine-Learning

In this project I used ML modeling and data analysis to predict ad clicks and significantly improve ad campaign performance, resulting in a 43.3% increase in profits. The selected model was Logistic Regression. The insights provided recommendations for personalized content, age-targeted ads, and income-level targeting, enhancing marketing strategy.

Language: Jupyter Notebook - Size: 4.54 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

FadekemiAkinduyile/Salary-Prediction-Regression-Project

Data Analysis and Machine Learning Project

Language: Jupyter Notebook - Size: 1.97 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

FadekemiAkinduyile/Effect-of-Mental-Health-on-Students-CGPA

Machine Learning Project

Language: Jupyter Notebook - Size: 297 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

LinggarM/Pima-Indians-Diabetes-Classification

Pima Indians Diabetes Classification using various supervised algorithms with feature importance

Language: Jupyter Notebook - Size: 852 KB - Last synced at: 2 months ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

travisyardley/churn_predictionmodel

Employee Prediction Analysis with Scikit-learn.

Language: Jupyter Notebook - Size: 475 KB - Last synced at: over 1 year ago - Pushed at: about 3 years ago - Stars: 0 - Forks: 0

colettebarca/collegeFootball

R Language. Code Files & Written Report. A brief overview of the project's goals and outcomes is given below.

Size: 452 KB - Last synced at: over 1 year ago - Pushed at: almost 3 years ago - Stars: 1 - Forks: 0

storieswithsiva/Machine-Learning-AB-Testing

📲🗜Experience how to implement Machine Learning for A/B Testing,Create a Split Object, and then Extract the Training and Testing sets🖥

Language: Jupyter Notebook - Size: 275 KB - Last synced at: over 1 year ago - Pushed at: almost 5 years ago - Stars: 2 - Forks: 2

sharmaroshan/Heart-UCI-Dataset

Analyzing the Features which leads to heart diseases and visualizing the models' performance and important features using eli5, shap and pdp.

Language: Jupyter Notebook - Size: 1.86 MB - Last synced at: over 1 year ago - Pushed at: almost 6 years ago - Stars: 8 - Forks: 16

north0n-FI/Predicting-terrorism-in-Europe-through-Decision-Trees-and-Random-Forests

Given enough data, could we make predictions on whether a terrorist attack will be successful, or not? This analysis aims to do just that using Decision Trees and Random Forests created with scikit-learn. (Python)

Language: Jupyter Notebook - Size: 741 KB - Last synced at: over 1 year ago - Pushed at: about 7 years ago - Stars: 2 - Forks: 2

now-youre-gittin-it/attrition-analysis

Predict the attrition (Yes/No) of employees, identify factors significantly impacting it, and finally state recommendations on how to mitigate the attrition.

Language: Jupyter Notebook - Size: 577 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

tvinitha/Customer-Conversion-Prediction

aims to predict customer conversion for an insurance company. Using historical data, we will develop a machine learning model that can identify which customers are most likely to purchase a policy.

Language: Jupyter Notebook - Size: 1.77 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

liewchooichin/ml_pipeline 📦

ML Pipeline. Detail documentation of the project in README. Click on actions to see the script.

Language: HTML - Size: 857 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

badhonparvej481/Feature-Selection_ML

Language: Jupyter Notebook - Size: 787 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

erikerlandson/1-pass-data-science

Demo notebook and data for Spark Summit Dublin 2017: One-Pass Data Science with Generative T-Digests

Language: Jupyter Notebook - Size: 34.4 MB - Last synced at: 3 months ago - Pushed at: over 7 years ago - Stars: 1 - Forks: 0

SanghyunKim1/Hitting-vs-Pitching-vs-Fielding-vs-Baserunning

Hitting vs Pitching vs Fielding vs Baserunning (Feature Importance)

Language: Python - Size: 2.24 MB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0

NatenaelTBekele/Credit-Card-Users-Churn-Prediction

Classification model that will help the bank improve its services so that customers do not renounce their credit cards

Language: Jupyter Notebook - Size: 8.05 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

rebelosa/feature-importance-neural-networks

Variance-based Feature Importance in Neural Networks

Language: Jupyter Notebook - Size: 42 KB - Last synced at: over 1 year ago - Pushed at: over 5 years ago - Stars: 26 - Forks: 14

2021-InternshipBLR/ml-data-prediction-mindsdb-python

Experimenting with MindsDB & Python Classification Algorithms

Language: Jupyter Notebook - Size: 727 KB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 1

Simrankumaran/covid_mindsdb_analysis

Covid data analysis using Logistic regression

Language: Jupyter Notebook - Size: 263 KB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 0 - Forks: 1

Pranjali1049/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: 1.71 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

Sweekwang/golabel

A website to explore biological relationships between Arabidopsis thailiana genetic characteristics.

Language: JavaScript - Size: 3.39 GB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 1

elkronos/fs_py

Feature selection functions for python.

Language: Python - Size: 101 KB - Last synced at: about 2 months ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

thierrygrimm/customer-churn

Project to identify credit card customers that are most likely to churn.

Language: Jupyter Notebook - Size: 2.61 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

vafaei-ar/feature-importance

This repository helps to analyze feature importance in data tables.

Size: 1.95 KB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0

Niranjan-stat/Telco-Churn-Analysis

Predicting churn among US telecom customers using Logistic Regression, Random Forest, Support Vector Machine and XG Boost in Python. Hyperparameter tuning using Random Grid search CV. Finding features of importance.

Language: Jupyter Notebook - Size: 3.07 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

parantapa/integrated-directional-gradients

Implementation of the Integrated Directional Gradients method for Deep Neural Network model explanations.

Language: Python - Size: 212 KB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 4 - Forks: 0

hxu47/Feature-Importance

Investigation of various feature importance strategies.

Language: Jupyter Notebook - Size: 3.4 MB - Last synced at: over 1 year ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

YousefGh/kmeans-feature-importance

Adding feature_importances_ property to sklearn.cluster.KMeans class

Language: Jupyter Notebook - Size: 2.76 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 55 - Forks: 19

hanfei1986/Interpret-feature-importance-using-SHAP

SHAP is a fancy tool for interpreting feature importance in machine learning tasks. This Jupyter notebook gives a demonstration.

Language: Jupyter Notebook - Size: 18.1 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

kuz/Spectral-signatures-of-perceptual-categorization-in-human-cortex

Language: MATLAB - Size: 1.22 MB - Last synced at: almost 2 years ago - Pushed at: over 5 years ago - Stars: 3 - Forks: 0

KishorAlagappan/customer-conversion-prediction-app

🚀 Revolutionize customer targeting with a predictive ML model that optimizes insurance subscription. 🎯📊

Language: Jupyter Notebook - Size: 4.73 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0

SkadiEye/deepTL

Deep Treatment Learning (R)

Language: R - Size: 3.72 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 13 - Forks: 1

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: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

fredyyyya/AB-Testing-and-Experiment-Design-Project

MSBA Big Data course project

Language: Jupyter Notebook - Size: 5.75 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

johnwslee/fine_dust_analysis

Study on Relationship between Fine Dust and Weather

Language: Jupyter Notebook - Size: 48.4 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

elshaabigail/Apps-Store-Properties-Prediction

A project aimed at predicting variables of interest within the dataset.

Language: Jupyter Notebook - Size: 377 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

alifrmf/Customer-Segmentation-Using-Clustering-Algorithms

Customer Segmentation Using Unsupervised Machine Learning Algorithms

Language: Jupyter Notebook - Size: 74.3 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 8 - Forks: 0

RBM-D-Xundullah/ENS-2Y-4P-Predictive-Maintenance-in-Photovoltaic-Systems-Using-Ensemble-ML-Empirical-Analysis

The research utilizes a 99.9kW PV system dataset, with a diverse set of features such as DC voltage, DC current, instantaneous power genera- tion, power factor, and frequency. Ensemble machine learning algorithms including RandomForest, XGBoost, CatBoost, and LightGBM were deployed to forecast the regular maintenance needs of the PV system.

Language: Jupyter Notebook - Size: 120 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

Jakob-Bach/Meta-Learning-Feature-Importance

Code for the suspended paper/project "Meta-Learning Feature Importance".

Language: Python - Size: 19.5 KB - Last synced at: about 1 year ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0

ashrafalaghbari/ProBHP

An AI-powered app for flowing bottom-hole pressure estimation and analysis in oil wells with multiphase flow.

Language: Jupyter Notebook - Size: 3.3 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0

lylakirati/footwear-display-prices

The Effects of Footwear Product Displays on Prices

Language: Jupyter Notebook - Size: 14.6 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

acurioussid/Kidney-Disease-Classification

Develop a classification model that can accurately diagnose the presence of kidney disease in a person based on their medical test results. The model will then identify which factors are the most influential in determining a person's chances of developing kidney disease.

Language: Jupyter Notebook - Size: 3.33 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

martins-jean/Credit-Card-Approvals

Learn various ways to select your features.

Size: 384 KB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

archd3sai/Predictive-Maintenance-of-Aircraft-Engine

In this project I aim to apply Various Predictive Maintenance Techniques to accurately predict the impending failure of an aircraft turbofan engine.

Language: Jupyter Notebook - Size: 23.1 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 80 - Forks: 33

jpmorganchase/cf-shap-facct22

Counterfactual Shapley Additive Explanation: Experiments

Language: Jupyter Notebook - Size: 1.33 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 3

FeatureHub-AI/FeatureHub

The most comprehensive library of AI/ML features across multiple domains. Our goal is to create a dataset that serves as a valuable resource for researchers and data scientists worldwide

Size: 221 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 6 - Forks: 3

lhkhiem28/Enhancing-Vietnamese-Sentiment-Analysis-with-Ensemble-Networks

This is the official source code of our IEA/AIE 2021 paper

Language: Python - Size: 155 MB - Last synced at: about 2 years ago - Pushed at: about 4 years ago - Stars: 4 - Forks: 1

rezacsedu/OncoNetExplainer

OncoNetExplainer: Explainable Prediction of Cancer Types Based on Gene Expression Data

Language: Jupyter Notebook - Size: 5.09 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 6 - Forks: 4

pierreolivierbonin/How-to-Get-Good-Beer-Review-Scores-A-Short-Machine-Learning-Project

In this project, I build an ML model to predict the scores of beer reviews and extract the most important features.

Language: Python - Size: 8.12 MB - Last synced at: 4 months ago - Pushed at: about 3 years ago - Stars: 0 - Forks: 0

adiag321/Prediction-and-Diagnosis-of-Heart-Disease-in-Patients

In this project, we predict if the person having a heart disease or not based on the several factors.

Language: Jupyter Notebook - Size: 2.92 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 1

abhinav-neil/customer-churn

Analyze and predict bank customer churn using various classification algorithms

Language: Jupyter Notebook - Size: 394 KB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 1 - Forks: 0

alexjmanlove/feature-importance-in-binary-classification-tasks

Exploring a strategy to identify feature importance in classification problems.

Language: Jupyter Notebook - Size: 7.74 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

adacanaydin/Prison-Covid-USA-2022

Analysis of Covid-19 Pandemic in American Prisons: neo4j, ML, feature importance.

Language: Jupyter Notebook - Size: 6.44 MB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

kpsijil2/Cement-Manufacturing

Predicting cement strength

Language: HTML - Size: 2.32 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

akokotis/conversion-influencers

predictive model to output a list of features that influence whether or not a searching customer decides to purchase a product

Language: R - Size: 273 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

alescrnjar/SalientFeat

Interpretable Deep Classification of Categorical Data

Language: Python - Size: 489 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

rochitasundar/Twitter-Sentiment-Analysis

Data consists of tweets scrapped using Twitter API. Objective is sentiment labelling using a lexicon approach, performing text pre-processing (such as language detection, tokenisation, normalisation, vectorisation), building pipelines for text classification models for sentiment analysis, followed by explainability of the final classifier

Language: Jupyter Notebook - Size: 3.71 MB - Last synced at: about 2 years ago - Pushed at: about 3 years ago - Stars: 3 - Forks: 0

ecorradini/NAFER

Software to compute Feature Relevance and Sensitivity of classification models.

Language: Python - Size: 188 KB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

MichaelAlexanderBryant/vehicle-price-prediction

An end-to-end project to analyze and model vehicle sale price data then productionize the best model to help people select a price to sell their vehicle.

Language: Python - Size: 872 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0

Eugene-Ovcharenko/COVID_reg

COVID-19 outcome prediction models based on machine learning algorithms. The unique feature is a custom cross-validation strategy based on the three clinical datasets of age- and gender-matched patients.

Language: Python - Size: 624 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

Sudhir22/conformalInference

Conformal Inference tools using python

Language: Python - Size: 43 KB - Last synced at: 5 months ago - Pushed at: about 5 years ago - Stars: 3 - Forks: 0

nestordemeure/permutationImportance

Feature importance by the permutation method (for fastai V1)

Language: Python - Size: 3.91 KB - Last synced at: about 2 years ago - Pushed at: about 5 years ago - Stars: 5 - Forks: 0

zahmed333/Public-Opinion-Qatar-World-Cup

Python Sentiment Analysis on the Qatar World Cup. Includes usage of Random Forrest model, feature importance, confusion matrix, and more.

Language: Jupyter Notebook - Size: 5.6 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

jpmorganchase/cf-shap

Counterfactual SHAP: a framework for counterfactual feature importance

Language: HTML - Size: 713 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 5 - Forks: 2

schatzederwelt/stock-prices-cars

Прогнозирование рыночной стоимости автомобилей

Language: Jupyter Notebook - Size: 380 KB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

schatzederwelt/taxi-demand-prediction

Прогнозирование спроса на такси

Language: Jupyter Notebook - Size: 1.01 MB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

neural-tangjie/NTJ-AIMed_3_Treatment

:octocat: This repository contains the notes, codes, assignments, quizzes and other additional materials about the course "AI for Medical Treatment" from DeepLearning.AI Coursera.

Size: 9.77 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

kntb0107/hyperparameter-tuning-with-logistic-regression

Project made for Optimisation and Deep Learning course.

Language: Jupyter Notebook - Size: 1.01 MB - Last synced at: about 1 year ago - Pushed at: about 3 years ago - Stars: 1 - Forks: 0

msoczi/clustfeatimp

Module for measuring feature importance for any clustering method.

Language: Python - Size: 370 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 2

FMatti/ALE-LSD

Feature importance analysis by accumulated local effects (ALE) in photoacoustic oximetry by learned spectral decoloring (LSD).

Language: Jupyter Notebook - Size: 67.3 MB - Last synced at: about 2 years ago - Pushed at: almost 4 years ago - Stars: 2 - Forks: 1

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

datatrigger/interpretable_machine_learning

Getting explanations for predictions made by black box models.

Language: Jupyter Notebook - Size: 4.25 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

AhmetZamanis/Kaggle-House-Prices-Regression-FeatureEng

Feature engineering, selection and XGBoost modeling for the Kaggle House Prices Regression competition.

Size: 570 KB - Last synced at: 3 months ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

HarryChenTw/heart-disease-prediction-and-analysis

Heart Disease Prediction and Analysis

Language: Jupyter Notebook - Size: 1.96 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 1 - Forks: 0

Neetz78/AnomalyDetection

Anomaly detection on Biosensor waveform using Deep neural networks and KShape clustering.

Language: Jupyter Notebook - Size: 9.05 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0

Neetz78/HDFS_anomaly

Performed data mining on HDFS log to gather important features to detect anomalies in the error logs.

Size: 8.7 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0

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

UnixJunkie/orrandomForest

OCaml wrapper to the R randomForest package

Language: OCaml - Size: 374 KB - Last synced at: about 2 months ago - Pushed at: about 3 years ago - Stars: 3 - Forks: 0

uzairahmadxy/email_marketing_causal_analysis

Statistical analysis to see effectiveness of email marketing campaign. Used regression, DoWhy & CausalML to calculate treatment effects. Feature importance & CATE, ITEs.

Language: Jupyter Notebook - Size: 828 KB - Last synced at: about 1 month ago - Pushed at: about 3 years ago - Stars: 0 - Forks: 0

eahussein/multiClass_astro

A multi classification problem on astronomy data, where the goal is to classify astronomical objects named (Quasars, stars, Galaxies)) using machine learning. The data used contains almost 288 features, the rebo has 3 tutorials that can help participants do the following

Language: Jupyter Notebook - Size: 8.44 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0

h4harsimran/Price_prediction

My submission to Housing price prediction competition on kaggle using XGBoost, Custom encoding, Kfold validation, Feature importance

Language: Jupyter Notebook - Size: 66.6 MB - Last synced at: almost 2 years ago - Pushed at: about 3 years ago - Stars: 0 - Forks: 0

Pradnya1208/Credit-card-fraud-detection-using-ensemble-learning-predictive-models

The Aim of this project is used to identify whether a new transaction is fraudulent or not.

Language: Jupyter Notebook - Size: 2.61 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0

Pradnya1208/Bank-customers-churn-prediction

our goal for this project is to predict the churn probability of a customer using machine learning classification techniques.

Language: Jupyter Notebook - Size: 3.23 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 1

priyanka2802/Lead-Scoring-Case-Study

Data Science Case Study: To help X Education select the most promising leads (Hot Leads), i.e. the leads that are most likely to convert into paying customers.

Language: Jupyter Notebook - Size: 2.26 MB - Last synced at: about 2 years ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 0

zemlyansky/importance

Permutation feature importance

Language: JavaScript - Size: 58.6 KB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 2 - Forks: 0

RamnathKumar181/Lending-Club-Analysis

We create a model using the gradient boosting algorithm to cut down on the noise and improve performance. This work was done during an informal project under Prof. Yaganti while studying at BITS.

Language: Python - Size: 190 KB - Last synced at: about 2 years ago - Pushed at: over 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