433 Open source projects that are alternatives of or similar to Dc Hi_guides

MLBox is a powerful Automated Machine Learning python library.

2017第一届腾讯社交广告高校算法大赛Rank28_code

Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies

📒 Experiment tracking tool and model registry

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Open solution to the Santander Value Prediction Challenge 🐠

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머신러닝/딥러닝(PyTorch, TensorFlow) 전용 도커입니다. 한글 폰트, 한글 자연어처리 패키지(konlpy), 형태소 분석기, Timezone 등의 설정 등을 추가 하였습니다.

Building Decision Trees From Scratch In Python

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a solution for competition of kaggle `Human or Robot`

A full pipeline AutoML tool for tabular data

A curated list of gradient boosting research papers with implementations.

住房月租金预测大数据赛TOP1

Automated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning 🚀

[UNMAINTAINED] Automated machine learning for analytics & production

A library for debugging/inspecting machine learning classifiers and explaining their predictions

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

🌳 Stacked Gradient Boosting Machines

Stacked Generalization (Ensemble Learning)

The complete code and notebooks used for the ACM Recommender Systems Challenge 2019

Solution to Kaggle's PLAsTiCC Astronomical Classification Competition

文本分类基准测试

Bayesian Optimization and Grid Search for xgboost/lightgbm

Open solution to the Home Credit Default Risk challenge 🏡

H2O.ai Machine Learning Interpretability Resources

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pure Go implementation of prediction part for GBRT (Gradient Boosting Regression Trees) models from popular frameworks

本人多次机器学习与大数据竞赛Top5的经验总结，满满的干货，拿好不谢

Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.

State-of-the art Automated Machine Learning python library for Tabular Data

Nyoka is a Python library to export ML/DL models into PMML (PMML 4.4.1 Standard).

A collection of research papers on decision, classification and regression trees with implementations.

Scalable machine 🤖 learning for time series forecasting.

Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

Performance of various open source GBM implementations

A package that makes it trivial to create and evaluate machine learning pipeline architectures.

Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.

A 100%-Julia implementation of Gradient-Boosting Regression Tree algorithms

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Earthquake Prediction Challenge with LightGBM and XGBoost

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Predict people interest in renting specific NYC apartments. The challenge combines structured data, geolocalization, time data, free text and images.

datascienv is package that helps you to setup your environment in single line of code with all dependency and it is also include pyforest that provide single line of import all required ml libraries

REST web service for the true real-time scoring (<1 ms) of Scikit-Learn, R and Apache Spark models

Archlinux PKGBUILDs for Data Science, Machine Learning, Deep Learning, NLP and Computer Vision

Automatic machine learning for tabular data. ⚡🔥⚡

Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/

用户贷款风险预测

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

A book about machine learning, statistics, and data mining for heliophysics

👨🏽‍🏫You can learn about anything over here. What Giveaways I do and why it's important in today's modern world. Are you interested in Giveaway's?🔋

потоковый курс "Машинное обучение и анализ данных (Machine Learning and Data Mining)" на факультете ВМК МГУ имени М.В. Ломоносова

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A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

Analyzing the Drugs Descriptions, conditions, reviews and then recommending it using Deep Learning Models, for each Health Condition of a Patient.

CIKM 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.

MetaSRA: normalized sample-specific metadata for the Sequence Read Archive

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