tensorflow kaggle house price[Done] Master version: developed the stacked regression (score 0.11, top 5%) based on (xgboost, sklearn). Branch v1.0: developed linear regression (score 0.45) based on Tensorflow
Stars: ✭ 25 (-78.45%)
XgboostScalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
Stars: ✭ 22,017 (+18880.17%)
Hyperparameter hunterEasy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
Stars: ✭ 648 (+458.62%)
Arch-Data-ScienceArchlinux PKGBUILDs for Data Science, Machine Learning, Deep Learning, NLP and Computer Vision
Stars: ✭ 92 (-20.69%)
Cikm analyticup 2017CIKM AnalytiCup 2017 is an open competition that is sponsored by Shenzhen Meteorological Bureau, Alibaba Group and CIKM2017. Our team got the third place in the first phrase. And in the second phrase we got the fourth place.
Stars: ✭ 66 (-43.1%)
Kaggle-Competition-SberbankTop 1% rankings (22/3270) code sharing for Kaggle competition Sberbank Russian Housing Market: https://www.kaggle.com/c/sberbank-russian-housing-market
Stars: ✭ 31 (-73.28%)
mloperatorMachine Learning Operator & Controller for Kubernetes
Stars: ✭ 85 (-26.72%)
KfservingServerless Inferencing on Kubernetes
Stars: ✭ 809 (+597.41%)
diabetes use caseSample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/
Stars: ✭ 22 (-81.03%)
Allstate capstoneAllstate Kaggle Competition ML Capstone Project
Stars: ✭ 72 (-37.93%)
HumanOrRobota solution for competition of kaggle `Human or Robot`
Stars: ✭ 16 (-86.21%)
OpenscoringREST web service for the true real-time scoring (<1 ms) of Scikit-Learn, R and Apache Spark models
Stars: ✭ 536 (+362.07%)
target-and-marketA data-driven tool to identify the best candidates for a marketing campaign and optimize it.
Stars: ✭ 19 (-83.62%)
Dc Hi guides[Data Castle 算法竞赛] 精品旅行服务成单预测 final rank 11
Stars: ✭ 83 (-28.45%)
Mli ResourcesH2O.ai Machine Learning Interpretability Resources
Stars: ✭ 428 (+268.97%)
secure-xgboostSecure collaborative training and inference for XGBoost.
Stars: ✭ 80 (-31.03%)
kserveServerless Inferencing on Kubernetes
Stars: ✭ 1,621 (+1297.41%)
DeeplearningPython for《Deep Learning》,该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现
Stars: ✭ 4,020 (+3365.52%)
TgboostTiny Gradient Boosting Tree
Stars: ✭ 302 (+160.34%)
Leavespure Go implementation of prediction part for GBRT (Gradient Boosting Regression Trees) models from popular frameworks
Stars: ✭ 261 (+125%)
MlboxMLBox is a powerful Automated Machine Learning python library.
Stars: ✭ 1,199 (+933.62%)
HyperGBMA full pipeline AutoML tool for tabular data
Stars: ✭ 172 (+48.28%)
Sci PypeA Machine Learning API with native redis caching and export + import using S3. Analyze entire datasets using an API for building, training, testing, analyzing, extracting, importing, and archiving. This repository can run from a docker container or from the repository.
Stars: ✭ 90 (-22.41%)
XGBoostLSSAn extension of XGBoost to probabilistic forecasting
Stars: ✭ 182 (+56.9%)
Data Science CompetitionsGoal of this repo is to provide the solutions of all Data Science Competitions(Kaggle, Data Hack, Machine Hack, Driven Data etc...).
Stars: ✭ 572 (+393.1%)
Home Credit Default RiskDefault risk prediction for Home Credit competition - Fast, scalable and maintainable SQL-based feature engineering pipeline
Stars: ✭ 68 (-41.38%)
Rong360用户贷款风险预测
Stars: ✭ 489 (+321.55%)
kaggle-codeA repository for some of the code I used in kaggle data science & machine learning tasks.
Stars: ✭ 100 (-13.79%)
Sigmoidal aiTutoriais de Python, Data Science, Machine Learning e Deep Learning - Sigmoidal
Stars: ✭ 103 (-11.21%)
featurewizUse advanced feature engineering strategies and select best features from your data set with a single line of code.
Stars: ✭ 229 (+97.41%)
TpotA Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Stars: ✭ 8,378 (+7122.41%)
FeatranA Scala feature transformation library for data science and machine learning
Stars: ✭ 420 (+262.07%)
recsys2019The complete code and notebooks used for the ACM Recommender Systems Challenge 2019
Stars: ✭ 26 (-77.59%)
Apartment-Interest-PredictionPredict people interest in renting specific NYC apartments. The challenge combines structured data, geolocalization, time data, free text and images.
Stars: ✭ 17 (-85.34%)
DrishtiReal time eye tracking for embedded and mobile devices.
Stars: ✭ 325 (+180.17%)
Mljar SupervisedAutomated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning 🚀
Stars: ✭ 961 (+728.45%)
AutovizAutomatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
Stars: ✭ 310 (+167.24%)
DtreevizA python library for decision tree visualization and model interpretation.
Stars: ✭ 1,857 (+1500.86%)
BtctradingTime Series Forecast with Bitcoin value, to detect upward/down trends with Machine Learning Algorithms
Stars: ✭ 99 (-14.66%)
Predicting real estate prices using scikit LearnPredicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)
Stars: ✭ 78 (-32.76%)
Xgboost Predictor JavaPure Java implementation of XGBoost predictor for online prediction tasks.
Stars: ✭ 302 (+160.34%)