ShraddhaPChaudhari/Breast_Cancer_Detection

Breast cancer detection app using machine learning XG-BOOST model. Model deployment using python and flask.

Language: Tcl - Size: 4.79 MB - Last synced: 6 days ago - Pushed: about 3 years ago - Stars: 0 - Forks: 0

NCMBianchi/DrugRepurposing Fork of carmenreep/DrugRepurposing

Automated drug repurposing workflow for rare diseases – using Flask, Monarch API, DGIdb API and XGboost.

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peijin0405/ML-XGBoostModel-for-Deal-and-User-Churn-Forecast

This project employs XGBoost regression and XGBoost classifier model to predict user order and user churn on online travel agency data. Reach 97% prediction accuracy.

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jakemaz66/EntityResolution

An Entity Resolution project deploying a doctor-to-grant XGBoost classifier using Vector Search with HNSW Graphs

Language: Python - Size: 87.9 KB - Last synced: 16 days ago - Pushed: 16 days ago - Stars: 0 - Forks: 0

Akash1070/Deploying-Machine-Learning-Models-via-Microsoft-Azure

Deploying Flight Price Prediction via Microsoft Azure

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Akash1070/Flight-Price-Predicting---Heroku

Flight Price Prediction Model Deployment IN Heroku

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Akash1070/BigMart-Sales-Prediction-

Building BigMart Sales Prediction

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aarushi-vermaa/airbnb_price_occupancy_revenue_prediction

Building a model to predict airbnb price and future occupancy bucket to estimate revenue for future investors

Language: Jupyter Notebook - Size: 279 MB - Last synced: about 2 months ago - Pushed: about 2 years ago - Stars: 2 - Forks: 2

JovanLiem/VehiclePricePrediction

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Sarthak-Mohapatra/US-Airlines-Tweets-Sentiment-Analysis

Classifying a tweet as positive, neutral, or negative sentiment using Natural Language Processing (CBOW approaches) and Traditional Machine Learning Algorithms.

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alexdatadesign/lfp_soc_ml

LiFePo4(LFP) Battery State of Charge (SOC) estimation from BMS raw data

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omerfarukeker/The-Complete-Journey

The Complete Journey Dataset: Churn Prediction

Language: Jupyter Notebook - Size: 623 KB - Last synced: 4 months ago - Pushed: about 4 years ago - Stars: 7 - Forks: 3

Muhammad-Talha4k/House-Price-Prediction

House Price Prediction using Xgboost model in python

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Mawbhe/Predicting-hospital-admission

ED Triage prediction

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tadedoyinsola/Air-Quality-Project

This repository contains the AirQo Low -cost Quality monitor calibration challenge, the codes and readme files after data pre-processing and predictive modelling.

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YoweioY/Product_demand_forecast

利用機器學習方法預測產品的需求量

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closedloop-ai/cv19index

COVID-19 Vulnerability Index

Language: Python - Size: 7.13 MB - Last synced: about 1 month ago - Pushed: over 1 year ago - Stars: 89 - Forks: 37

chollette/Liver-Disease-Classification-Azure-ML-Capstone-Project

This is a Liver Disease Machine Learning Classification Capstone Project in fulfillment of the Udacity Azure ML Nanodegree. In this project, you will learn to deploy a machine learning model from scratch. The files and documentation with experiment instructions needed for replicating the project, is provided for you.

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MsTao-68/IMDB-NLP-Classification

# 自然语言处理 IMDB 情感分析数据集任务

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MsTao-68/Debt-Churn-Data-Analysis

使用比赛方提供的脱敏数据，进行客户信贷流失预测。

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naikaly/credef

Credit Default Approximation for Unsecured Lending Built Machine Learning Classification models (Random Forest, LGBM, XGBoost) in Python to assess the probability of credit defaults.

Language: Python - Size: 18.6 KB - Last synced: 5 months ago - Pushed: over 2 years ago - Stars: 0 - Forks: 0

IanDublew/xGBoost-Sports-betting-Predictor

Sports betting match predictor

Language: Jupyter Notebook - Size: 293 KB - Last synced: 5 months ago - Pushed: 5 months ago - Stars: 1 - Forks: 0

DHwass/XGBoost-on-Home-Data-KAGGLE

In this project, XGBoost is applied to forecast real estate prices using the Boston Housing Dataset. The primary aim is to create an effective predictive model, assess its accuracy through metrics like Mean Absolute Error (MAE), and refine its performance by tuning hyperparameters with HYPEROPT.

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Ideas2IT/datascience-lab

Data Science Experiments Repository of Ideas2IT

Language: Jupyter Notebook - Size: 464 KB - Last synced: about 2 months ago - Pushed: about 4 years ago - Stars: 2 - Forks: 1

arminZolfaghari/Diabetes-Classification-XGBoost

Data Mining Course Project - Diabetes Classification with XGBoost - Winter 2022

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srivatsakoustub/BIG-MART-SALES-PREDICTION

conducted in-depth analysis of a large dataset containing historical sales data, product attributes and store information. --> Developed and implemented machine learning models, including regression algorithms, to accurately forecast sales for different products and stores and we finally obtained a better result through random forest regression alg

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coolmunzi/end_to_end_ml-fitbit_calorie_counter

This is an End to end Machine Learning project based on Flask APIs covering model training and prediction pipelines for finding calorie from fitbit band's data.

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Javihaus/Advanced-Time-series-analysis

Advance Time Series Analysis using Probabilistic Programming, Auto Regressive Neural Networks and XGBoost Regression.

Language: Jupyter Notebook - Size: 8.43 MB - Last synced: 7 months ago - Pushed: about 3 years ago - Stars: 6 - Forks: 2

aotantawy/Monefy

A stock prediction using machine learning

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Keivaly/Xgboost-RandomForest

Contains solution of Jigsaw academy's final capstone project, mostly to indicate coding prowess and analytics methodology followed for recruiters

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shivangi-975/Machine_Learning

Machine Learning Concepts and Algorithms.

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SanyaGoyal/Allstate-Insurance-Predicting-Claim-Severity-Xgboost-ML

This is a solution to a Kaggle competition on predicting claim severity for Allstate Insurance using the Extreme Gradient Boosting (XgBoost) algorithm in R

Language: R - Size: 17.1 MB - Last synced: 7 months ago - Pushed: over 6 years ago - Stars: 0 - Forks: 8

g-aditi/customer-personality-analysis

Using a Kaggle dataset, customer personality was analysed on the basis of their spending habits, income, education, and family size. K-Means, XGBoost, and SHAP Analysis were performed.

Language: Jupyter Notebook - Size: 1.68 MB - Last synced: 7 months ago - Pushed: over 2 years ago - Stars: 3 - Forks: 1

GeorgeOduor/bigmart

Predictive modeling

Size: 236 KB - Last synced: 7 months ago - Pushed: over 5 years ago - Stars: 0 - Forks: 0

prgrmcode/tr-earthquake-predictor

Turkey Earthquake Prediction 🌍📊: Unleashing AI/ML powers in Python for seismic forecasts. #MachineLearning #Python #DataScience 🤖

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NatenaelTBekele/cardiovascular_disease_prediction

Aim of the problem is to detect the presence or absence of cardiovascular disease in person based on the given features

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Mfundo-debug/Bank_Customer_churn

Bank Customer Churn Prediction

Language: Jupyter Notebook - Size: 1.8 MB - Last synced: 25 days ago - Pushed: 11 months ago - Stars: 0 - Forks: 0

olesyamba/ICvsML

Usual linear regression or XGBoost? Combo! Or how I was investigating the impact of intellectual capital on NASDAQ-100 capitalization during 2 years.

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Ravjot03/Parkinsons-Disease

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Ravjot03/Machine-Learning-Models

Language: Jupyter Notebook - Size: 1.97 MB - Last synced: 8 months ago - Pushed: about 3 years ago - Stars: 0 - Forks: 0

jimschacko/Hotel-reservation-Prediction-using-XGBoost

Hotel Reservation Prediction using XGBoost

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pranaya-mathur/Sentiment-Classification

Implemented Machine Learning Models on Amazon Fine Food Reviews Data Set

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ashcode028/Music-Genre-Classification

Classifying audio files using ML algorithms.

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clementetienam/Data_Driven_MPC_Controller_Using_CCR

Language: MATLAB - Size: 11.9 MB - Last synced: 9 months ago - Pushed: over 3 years ago - Stars: 1 - Forks: 2

TrilokiDA/analyticsVidhya

Language: Jupyter Notebook - Size: 469 KB - Last synced: 9 months ago - Pushed: 9 months ago - Stars: 0 - Forks: 1

alexarnold630/Dallas_Crime_Analysis_and_Prediction

Machine Learning Engine predicting Dallas crime incident status with visualization analysis using Tableau for crime time and locations.

Language: Jupyter Notebook - Size: 41.7 MB - Last synced: 9 months ago - Pushed: about 3 years ago - Stars: 1 - Forks: 1

h30306/Kaggle-Airbnb-New-User-Booking

Kaggle competition. Our proposed using Hierarchical XGBoosting model to predict the target country of customer preference

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ankitapiu/Mercedes-Benz-Greener-Manufacturing

Xboost algorithm Model

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HarigovindV10/Credit-Card-Fraud-Detection

A credit card fraud detection algorithm.

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ek0212/TCIA-Classification

Dichotomized classification of glioblastomas and low grade gliomas using publicly available data

Language: Jupyter Notebook - Size: 139 KB - Last synced: 9 months ago - Pushed: over 3 years ago - Stars: 0 - Forks: 0

4k11/Savorr

A website utilizing datasets trained using XGBoost algorithm to forecast sales in big mart with best possible accuracy in comparison to other existing models.

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nrgdoublex/TalkingData_challenge

models for TalkingData AdTracking Fraud Detection Challenge

Language: Python - Size: 5.86 KB - Last synced: 10 months ago - Pushed: about 6 years ago - Stars: 0 - Forks: 0

TanweerulHaque/VindiataBusinessCase-Study

A business case study to solve problems related to an airline startup using ML

Language: Jupyter Notebook - Size: 64.5 KB - Last synced: 10 months ago - Pushed: over 3 years ago - Stars: 0 - Forks: 0

datacrypto-analytics/crypto-analysis-cli

Analise todas as criptomoedas disponíveis na binance spot com algoritmos Machine Learning.

Language: Python - Size: 1.65 MB - Last synced: 4 days ago - Pushed: over 3 years ago - Stars: 5 - Forks: 2

keshavbhandari/Gredel

Automated R-Shiny based UI platform to create and deploy a XGBoost model on ANY dataset. Additionally it also includes black box interpretation techniques such as PDP, ALE Plots, permutation importance.

Language: HTML - Size: 1.04 MB - Last synced: 10 months ago - Pushed: almost 4 years ago - Stars: 1 - Forks: 1

lperconti/Visitation

Visitation Modeling - Capstone Project for Flatiron DataScience Bootcamp. In this project, I look at three winter resorts and utilize weather and event data to predict visitation for each resort. Uses Machine Learning (Regression) analysis to make predictions.

Language: Jupyter Notebook - Size: 21.3 MB - Last synced: 10 months ago - Pushed: over 2 years ago - Stars: 1 - Forks: 0

KindlyGentleman/DS-DA-Bank-Churn-Prediction

This repo contains a machine learning project for predicting bank customer churn using XGBoost. It includes data preprocessing, model training, and deployment as an API and Streamlit app in a Docker container. The repo also contains a report and images documenting the project.

Language: Jupyter Notebook - Size: 3.14 MB - Last synced: 10 months ago - Pushed: 10 months ago - Stars: 2 - Forks: 0

vishalv91/Customer-Analytics

The project concerns an international e-commerce company* based in the USA who want to discover key insights from their customer database. They want to use some of the most advanced machine learning techniques to study their customers.

Language: R - Size: 1.34 MB - Last synced: 3 months ago - Pushed: over 3 years ago - Stars: 4 - Forks: 5

RifkiOskar/Predict-Customer-Default

Loan Approval Analysis & Prediction

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urmipandya123/Road_Severity_Classification

Language: Jupyter Notebook - Size: 1.85 MB - Last synced: 29 days ago - Pushed: about 1 year ago - Stars: 0 - Forks: 0

nicoladisabato/online-shoppers-intention

Binary classification with Boosting ensemble algorithm

Size: 278 KB - Last synced: about 1 year ago - Pushed: almost 2 years ago - Stars: 1 - Forks: 0

ddS08/Detecting-Parkinsons-Disease

Language: Jupyter Notebook - Size: 983 KB - Last synced: 5 months ago - Pushed: 5 months ago - Stars: 1 - Forks: 1

stonecoldnicole/flip-or-skip

Machine learning models are used to determine whether a house is a good potential "flip" or not, using standard 70% rule.

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olaelshiekh/Heart_Disease_detection

World Health Organization has estimated 12 million deaths occur worldwide, every year due to Heart diseases. Half the deaths in the United States and other developed countries are due to cardio vascular diseases.

Language: Jupyter Notebook - Size: 5.56 MB - Last synced: 12 months ago - Pushed: over 2 years ago - Stars: 6 - Forks: 2

DiegoVallarino/MSc-and-PhD-studies-in-Survival

In this work I tested if there was an improvement in performance in the use of different survival models.

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asaficontact/project_floodlight

Crisis incidents caused by rebel groups create a negative influence on the political and economic situation of a country. However, information about rebel group activities has always been limited. Sometimes these groups do not take responsibility for their actions, sometimes they falsely claim responsibility for other rebel group’s actions. This has made identifying the rebel group responsible for a crisis incident a significant challenge. Project Floodlight aims to utilize different machine learning techniques to understand and analyze activity patterns of 17 major rebel groups in Asia (including Taliban, Islamic State, and Al Qaeda). It uses classification algorithms such as Random Forest and XGBoost to predict the rebel group responsible for organizing a crisis event based on 14 different characteristics including number of fatalities, location, event type, and actor influenced. The dataset used comes from the Armed Conflict Location & Event Data Project (ACLED) which is a disaggregated data collection, analysis and crisis mapping project. The dataset contains information on more than 78000 incidents caused by rebel groups that took place in Asia from 2017 to 2019. Roughly 48000 of these observations were randomly selected and used to develop and train the model. The final model had an accuracy score of 84% and an F1 Score of 82% on testing dataset of about 30000 new observations that the algorithm had never seen. The project was programmed using Object Oriented Programming in Python in order to make it scalable. Project Floodlight can be further expended to understand other crisis events in Asia and Africa such as protests, riots, or violence against women.

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jayita13/hackerearth-ML-challenge-pet-adoption

Final Rank - 81 out of 5060

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alanchn31/Data-Science-Portfolio

Personal Data Science Projects

Language: Jupyter Notebook - Size: 26.1 MB - Last synced: about 1 year ago - Pushed: about 1 year ago - Stars: 2 - Forks: 0

mddunlap924/Recommender-System

Multi-Objective Recommender System

Language: Python - Size: 332 KB - Last synced: about 1 year ago - Pushed: about 1 year ago - Stars: 0 - Forks: 0

aditya-167/Realtime-Earthquake-forecasting

Web application for earthquake prediction in a window of few future days. live data collection from https://earthquake.usgs.gov/

Language: HTML - Size: 69.3 MB - Last synced: about 1 year ago - Pushed: over 3 years ago - Stars: 1 - Forks: 2

jimschacko/Churn-Modelling-using-XGBoost

Churn Modelling using XGBoost

Language: Jupyter Notebook - Size: 1.01 MB - Last synced: 11 months ago - Pushed: over 1 year ago - Stars: 1 - Forks: 0

manasik29/Forecasting_Energy_Consumption_Project

Hourly Energy Consumption Forecasting

Language: Jupyter Notebook - Size: 20.5 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0

celeronCoder/heart_failure_prediction 📦

Heart Failure Prediction using Machine Learning

Language: Jupyter Notebook - Size: 179 KB - Last synced: about 1 year ago - Pushed: over 2 years ago - Stars: 0 - Forks: 0

rudrajit1729/Machine-Learning-Codes-And-Templates

Codes and templates for ML algorithms created, modified and optimized in Python and R.

Language: Python - Size: 21 MB - Last synced: about 1 year ago - Pushed: about 4 years ago - Stars: 4 - Forks: 3

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: about 1 year ago - Pushed: about 2 years ago - Stars: 3 - Forks: 0

Hutaf/Speech-Emotion-Recognition

Language: Jupyter Notebook - Size: 2.21 MB - Last synced: about 1 year ago - Pushed: over 3 years ago - Stars: 2 - Forks: 0

AaronFlore/Forecasting-Bitcoin-Prices

Forecasting Bitcoin Prices via ARIMA, XGBoost, Prophet, and LSTM models in Python

Language: Jupyter Notebook - Size: 1.03 MB - Last synced: about 1 year ago - Pushed: almost 3 years ago - Stars: 4 - Forks: 2

dysdsyd/kaggle-question-pairs-quora

My solution for Quora's Question Pair contest on Kaggle.

Language: Jupyter Notebook - Size: 276 KB - Last synced: about 1 year ago - Pushed: almost 7 years ago - Stars: 11 - Forks: 10

suhas004/Air-Quality-Index-Deployment-

Language: HTML - Size: 6.91 MB - Last synced: about 1 year ago - Pushed: about 1 year ago - Stars: 1 - Forks: 2

YashMuchhala/AInsurance

Machine Learning to Determine Auto-Insurance Premiums using Telematics

Language: Python - Size: 825 KB - Last synced: about 1 year ago - Pushed: about 2 years ago - Stars: 2 - Forks: 0

BibhuPrasadPanda97/Credit-Card-Default-Risk---AmExpert-CodeLab

Competition conducted by American Express on HackerEarth Platform to Predict Credit Card Defaulters by building Machine Learning Models for the given data.

Language: Jupyter Notebook - Size: 2.87 MB - Last synced: about 1 year ago - Pushed: over 2 years ago - Stars: 1 - Forks: 1

IamVaibhavsar/House_Price_Prediction

This project aims at predicting house prices (residential) in Ames, lowa, USA. The data set for this project has been taken from Kaggle's Housing Data Set Knowledge Competition. The Algorithms used in this project are XGBoost, Neural Network and Lasso Regression

Language: Jupyter Notebook - Size: 1.54 MB - Last synced: about 1 year ago - Pushed: about 4 years ago - Stars: 0 - Forks: 0

muhammadhaerul25/Machine-Learning-Haealthkathon-BPJS-2022

Language: Jupyter Notebook - Size: 313 KB - Last synced: 11 months ago - Pushed: over 1 year ago - Stars: 1 - Forks: 1

Amir79Naziri/DiabetesClassification_Project

Implementing a classifier for diabetes dataset with XGBOOST.

Language: Jupyter Notebook - Size: 542 KB - Last synced: 11 months ago - Pushed: over 1 year ago - Stars: 1 - Forks: 0

ankitAMD/NYTaxi_XG_Boost_Challenge-kaggle_challenge

I'm attempting the NYC Taxi Duration prediction Kaggle challenge. I'll by using a combination of Pandas, Matplotlib, and XGBoost as python libraries to help me understand and analyze the taxi dataset that Kaggle provides. The goal will be to build a predictive model for taxi duration time. I'll also be using Google Colab as my jupyter notebook. i will also predict without Google colab on normal system.

Language: Jupyter Notebook - Size: 24.8 MB - Last synced: about 1 year ago - Pushed: over 5 years ago - Stars: 6 - Forks: 3

kyaiooiayk/XGBoost-notes

Notes, tutorials, code snippets and templates focused on XGBoost for Machine Learning

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jeandsantos/predict_water_turbidity

Predict the quantity of turbidity, the level of product traces or suspended solids in the effluent, that will be returned in last rinsing phase during the cleaning of food and beverage industrial equipment

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rashmi-biswas/ML_Regression_Sales_Prediction

Retail Sales Prediction using Machine Learning Regression Models

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DthRazak/Dota2Project

Exploratory and Predictive analysis of the Dota 2 dataset

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AmitGairola/Python-Projects

This is a repository created for Python Projects

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An-Dongsun/Section2-Project

머신러닝 프로젝트 : 심장병 예측 모델 제작 및 해석

Language: Jupyter Notebook - Size: 95.1 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0

kgaleziowski/recommender-systems-content-based

Recommender Systems 2021/2022: Content Based Recommenders Project

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surdebmalya/Breast-Cancer-Analysis

This classification project is specifically focused on data visualization and feature selection. I got 96.49% accuracy here.

Language: Jupyter Notebook - Size: 1.68 MB - Last synced: about 1 year ago - Pushed: about 3 years ago - Stars: 1 - Forks: 1

cong-khai-nguyen/titanic-survival

Titanic

Language: Python - Size: 85.9 KB - Last synced: about 1 year ago - Pushed: about 2 years ago - Stars: 0 - Forks: 0

Zedstron/hands-gesture-detector

A python project which uses laptop webcam to detect hands by using mediapipe library and then perform some further processing to figgure out hand posture e.g. one, two or Left, Right, The postures are used to control different computer functions e.g desktop switch in windows or mouse control

Language: Python - Size: 33.2 KB - Last synced: about 1 year ago - Pushed: about 2 years ago - Stars: 0 - Forks: 0

renjmindy/COVID19-ChicagoCarCrashClassifier

Machine Learning - XGBoost, Random Forest, Decision Tree

Language: Jupyter Notebook - Size: 14.1 MB - Last synced: about 1 year ago - Pushed: about 2 years ago - Stars: 0 - Forks: 1

anjalysam/ATM_Transaction-data_analysis-

Find the best algorithm to analyze and predict the demand for cash withdrawals

Language: Jupyter Notebook - Size: 899 KB - Last synced: about 1 year ago - Pushed: over 3 years ago - Stars: 2 - Forks: 0

MitchellTesla/Max-Q Fork of arXiv-research/Quatm

Machine-Learning: eXtreme Gradient-Boosting Algorithm Stress Testing

Language: C++ - Size: 155 MB - Last synced: about 1 year ago - Pushed: almost 2 years ago - Stars: 7 - Forks: 0

SenSudi/EE-695-Applied-Machine-Learning

Implemented various ML algorithms with and without library functions. Final Project-->Application of LGBM, XGBoost, Catboost and SVC

Language: Jupyter Notebook - Size: 13.2 MB - Last synced: about 1 year ago - Pushed: about 3 years ago - Stars: 1 - Forks: 2

anantgupta129/XGBoost-for-Machine-Learning

XGBoost Model for Machine Learning implementation on breast cancer dataset in Python and churm modelling in R

Language: Jupyter Notebook - Size: 305 KB - Last synced: about 1 year ago - Pushed: over 3 years ago - Stars: 1 - Forks: 0