xgboost-model

There are 3 repositories under xgboost-model topic.

closedloop-ai / cv19index
COVID-19 Vulnerability Index
coronavirus coronavirus-analysis covid-19 covid19 ml xgboost-model
Language:Python 88
grtvishnu / Air-Pollution-Prediction-and-Forecasting
:octocat: Detection and Prediction of Air quality Index :octocat:
r catboost xgboost-model random-forest deep-neural-networks mlp data-analysis prophet-model time-series
Language:Jupyter Notebook 48
keisukeirie / quickdraw_prediction_model
this is my repository for the quick draw prediction model project
prediction-model quickdraw xgboost-model cnn-keras data-science
Language:Python 45
alexdatadesign / lfp_soc_ml
LiFePo4(LFP) Battery State of Charge (SOC) estimation from BMS raw data
battery battery-management-system bms lfp lifepo4 lifepo4-battery esphome inverter machine-learning state-of-charge xgboost-model xgboost-regression
Language:Jupyter Notebook 18
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/
earthquake-prediction xgboost-model event-series-analysis
Language:HTML 14
AaronFlore / Forecasting-Bitcoin-Prices
Forecasting Bitcoin Prices via ARIMA, XGBoost, Prophet, and LSTM models in Python
bitcoin machine-learning deep-learning finance time-series-forecasting prophet-model ltsm xgboost-model arima-forecasting model-comparison
Language:Jupyter Notebook 13
keisukeirie / Amazon_review_helpfulness_prediction
this is my repository for Amazon review helpfulness prediction model
prediction-model customer-reviews helpful-reviews amazon xgboost-model random-forest nmf nlp-machine-learning product-reviews
Language:Jupyter Notebook 11
dysdsyd / kaggle-question-pairs-quora
My solution for Quora's Question Pair contest on Kaggle.
kaggle lstm-model xgboost-model deep-learning
Language:Jupyter Notebook 10
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.
machine-learning classification azure-devops azure-pipelines liver-disease end-to-end-machine-learning xgboost-model liver-disease-dataset hyperparameter-tuning automl azure
Language:Jupyter Notebook 9
smritig19 / PCOS_Diagnosis_System
data-visualization machine-learning-algorithms pandas numpy matplotlib seaborn scikitlearn-machine-learning knn-classifier svc-model logistic-regression-classifier random-forest-classifier decision-tree-classifier xgboost-model catboost-model lightgbm mlxtend exploratory-data-analysis prediction data-preprocessing pcos
Language:Jupyter Notebook 9
Max-Q
MitchellTesla / Max-Q
Machine-Learning: eXtreme Gradient-Boosting Algorithm Stress Testing
neural-networks machine-learning-algorithms jupyter-notebooks python-3 arxiv-papers pytorch xgboost-algorithm xgboost-model xgboost-python xgboost-regression
Language:C++ 8
rudrajit1729 / Machine-Learning-Codes-And-Templates
Codes and templates for ML algorithms created, modified and optimized in Python and R.
datascience feature-extraction feature-selection regression-models regression-algorithms classification-algorithims kmeans-clustering hierarchical-clustering apriori-algorithm eclat-algorithm ucb thompson-sampling nlp-machine-learning ann cnn-classification kfold-cross-validation dimensionality-reduction xgboost-model parameter-tuning
Language:Python 8
project_floodlight
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.
xgboost-model random-forest classification-model crisis grid-search-hyperparameters acled python3 object-oriented-programming sklearn asia grid-search pandas matplotlib
Language:Jupyter Notebook 7
Advanced-Time-series-analysis
Javihaus / Advanced-Time-series-analysis
Advance Time Series Analysis using Probabilistic Programming, Auto Regressive Neural Networks and XGBoost Regression.
xgboost-model keras-neural-networks keras pytorch-implementation pymc3 probabilistic-programming time-series time-series-analysis
Language:Jupyter Notebook 7
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.
machine-learning data-science healthcare heart-disease heart-failure data-visualization eda modelling rfc xgboost-model logistic-regression
Language:Jupyter Notebook 7
omerfarukeker / The-Complete-Journey
The Complete Journey Dataset: Churn Prediction
churn churn-prediction the-complete-journey-dataset dunnhumby xgboost xgboost-algorithm xgboost-model xgb-classifier hyperparameter-optimization feature-extraction feature-engineering
Language:Jupyter Notebook 7
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.
nyc-taxi-dataset kaggle-competition fastest-routes xgboost visualization-image python knn-regression linear-regression random-forest feature-engineering python3 machine-learning deep-learning google-colab remote-server scikit-learn xgboost-model pandas numpy matplotlib
Language:Jupyter Notebook 6
ashcode028 / Music-Genre-Classification
Classifying audio files using ML algorithms.
machine-learning classification xgboost-model svm-model mlp-classifier audio-processing
Language:Jupyter Notebook 6
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.
machine-learning python kmeans-clustering kmeans xgboost xgboost-algorithm kmeans-clustering-algorithm xgboost-model shap-analysis shapley-additive-explanations customer-personality-analysis customer-personas
Language:Jupyter Notebook 6
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。
ann autogluon eda lightgbm machine-learning smote-oversampler smote-sampling stacking-classifier stacking-ensemble stratified-cross-validation stratified-sampling tabnet xgboost-model
Language:Jupyter Notebook 6
Pzugatti / House-Price-Prediction
By using feature engineering technique and XGBoost algorithm to predict house price
xgboost-model tabular-data advanced-regression feature-engineering python3
Language:Jupyter Notebook 6
alanchn31 / Data-Science-Portfolio
Personal Data Science Projects
data-science machine-learning exploratory-data-analysis feature-engineering random-forest xgboost-model logistic-regression image-classification style-transfer transfer-learning deep-learning convolutional-neural-networks scikit-learn pytorch keras tensorflow ethical-artificial-intelligence ethical-ai fairlearn
Language:Jupyter Notebook 5
arminZolfaghari / Diabetes-Classification-XGBoost
Data Mining Course Project - Diabetes Classification with XGBoost - Winter 2022
xgboost xgboost-model datamining preprocessing classification diabetes-classification
Language:Jupyter Notebook 5
datacrypto-analytics / crypto-analysis-cli
Analise todas as criptomoedas disponíveis na binance spot com algoritmos Machine Learning.
machine-learning xgboost matplotlib quantitative-finance cryptocurrency bitcoin ethereum binance binance-api binance-smart-chain machine-learning-algorithms xgboost-model xgboost-algorithm
Language:Python 5
Majd0507 / Machine-Learning
Machine learning tutorial with examples
machine-learning machine-learning-algorithms machinelearning machine-learning-api machine machine-learning-coursera machine-learning-library deep-learning convolutional-neural-networks artificial-neural-networks python spyder jupyter-notebook anaconda anaconda3 regression-algorithms classification-algorithm clustering-algorithm xgboost-algorithm xgboost-model
Language:Python 5
nickdcox / ml-linear-airfare-prediction
Project: What factors impact the accuracy of airfare prediction?
data-cleaning feature-engineering exploratory-data-analysis machine-learning linear-regression data-visualisation model-deployment python pandas sklearn xgboost-model lgbmregressor flask google-maps-api matplotlib
Language:HTML 4
shivamgupta7 / Amazon-Fine-Food-Reviews
Amazon Fine Food Reviews is classification Sentiment Analysis problem. Classify the positive and negative reviews given by Amazon users. Given some product-based features and related reviews in text data. Featuring data and apply various Machine Learning techniques to classify reviews.
tsne eda tf-idf w2v bow knn-classification naive-bayes-classifier amazon-fin logistic-regression svm-classifier decision-tree-classifier random-forest-classifier xgboost-model
Language:Jupyter Notebook 4
skyhuang1208 / kaggle-porto-safe-driver-prediction
won silver medal, 164th of 5169
kaggle kaggle-competition xgboost xgboost-model neural-network keras blending random-forest
Language:Jupyter Notebook 4
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.
machine-learning sagemaker xgboost-model house python
Language:HTML 4
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.
analytics data-science data-visualization datasets data-science-projects r customer-analytics ecommerce r-programming r-project logistic-regression support-vector-machines random-forest-classifier classification-algorithims data-modeling xgboost-model cluster-analysis ggplot2 twitter-sentiment-analysis on-time-delivery
Language:R 4
Akash1070 / BigMart-Sales-Prediction-
Building BigMart Sales Prediction
bigmart-sales-prediction decision-tree-regression exploratory-data-analysis feature-engineering linear-regression python3 random-forest-regression xgboost-model
Language:Jupyter Notebook 3
anjalysam / ATM_Transaction-data_analysis-
Find the best algorithm to analyze and predict the demand for cash withdrawals
linear-regression xgboost-model svm-regressor ann
Language:Jupyter Notebook 3
Madhav-Somanath / WindEnergyPredictor
Machine learning model built for IBM Hack 2020 challenge. ⚙️
time-series arima-model arma-model lasso-regression random-forest decision-trees xgboost-model
Language:Jupyter Notebook 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
regex lemmatization stemming-porters textblob tfidfvectorizer sentiment-classification stratified-sampling gridsearchcv pipeline linearsvc-model multinomial-naive-bayes random-forest xgboost-model feature-importance
Language:Jupyter Notebook 3
jimschacko / Churn-Modelling-using-XGBoost
Churn Modelling using XGBoost
churn-analysis churn-modeling churn-modelling churn-prediction classification data-science machine-learning scikit-learn xgboost xgboost-algorithm xgboost-classifier xgboost-model
Language:Jupyter Notebook 2
mddunlap924 / Recommender-System
Multi-Objective Recommender System
implicit kaggle-competition pairwise polars rapidsai recommender-system reranker xgboost-model
Language:Python 2

xgboost-model

closedloop-ai / cv19index

grtvishnu / Air-Pollution-Prediction-and-Forecasting

keisukeirie / quickdraw_prediction_model

alexdatadesign / lfp_soc_ml

aditya-167 / Realtime-Earthquake-forecasting

AaronFlore / Forecasting-Bitcoin-Prices

keisukeirie / Amazon_review_helpfulness_prediction

dysdsyd / kaggle-question-pairs-quora

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

smritig19 / PCOS_Diagnosis_System

MitchellTesla / Max-Q

rudrajit1729 / Machine-Learning-Codes-And-Templates

asaficontact / project_floodlight

Javihaus / Advanced-Time-series-analysis

olaelshiekh / Heart_Disease_detection

omerfarukeker / The-Complete-Journey

ankitAMD / NYTaxi_XG_Boost_Challenge-kaggle_challenge

ashcode028 / Music-Genre-Classification

g-aditi / customer-personality-analysis

MsTao-68 / Debt-Churn-Data-Analysis

Pzugatti / House-Price-Prediction

alanchn31 / Data-Science-Portfolio

arminZolfaghari / Diabetes-Classification-XGBoost

datacrypto-analytics / crypto-analysis-cli

Majd0507 / Machine-Learning

nickdcox / ml-linear-airfare-prediction

shivamgupta7 / Amazon-Fine-Food-Reviews

skyhuang1208 / kaggle-porto-safe-driver-prediction

stonecoldnicole / flip-or-skip

vishalv91 / Customer-Analytics

Akash1070 / BigMart-Sales-Prediction-

anjalysam / ATM_Transaction-data_analysis-

Madhav-Somanath / WindEnergyPredictor

rochitasundar / Twitter-Sentiment-Analysis

jimschacko / Churn-Modelling-using-XGBoost

mddunlap924 / Recommender-System