334 Open source projects that are alternatives of or similar to aws-machine-learning-university-dte

Automatic machine learning for tabular data. ⚡🔥⚡

🌳 Stacked Gradient Boosting Machines

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

A full pipeline AutoML tool for tabular data

Building Decision Trees From Scratch In Python

文本分类基准测试

A python library for decision tree visualization and model interpretation.

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

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

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

A curated list of gradient boosting research papers with implementations.

Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)

It's a github repo star predictor that tries to predict the stars of any github repository having greater than 100 stars.

Workshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles

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

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

Performance of various open source GBM implementations

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

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.

Repository for the AdaptiveRandomForest algorithm implemented in MOA 2016-04

Machine learning algorithm such as KNN,Naive Bayes,Logistic Regression,SVM,Decision Trees,Random Forest,k means and Truncated SVD on amazon fine food review

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

A tool for visualizing the structure and performance of Random Forests 🌳

Scalable machine 🤖 learning for time series forecasting.

Python code for common Machine Learning Algorithms

Machine Learning Lectures at the European Space Agency (ESA) in 2018

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

simple tutorial on Machine Learning with Scikitlearn

Machine learning for C# .Net

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

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

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

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

Material from "Random Forests and Gradient Boosting Machines in R" presented at Machine Learning Day '18

📈 Click-Through Rate Prediction using Logistic Regression and Tree Algorithms

Comparison tools

Top 5th percentile solution to the Kaggle knowledge problem - Bike Sharing Demand

[ICML 2019, 20 min long talk] Robust Decision Trees Against Adversarial Examples

A python library to build Model Trees with Linear Models at the leaves.

Kaggle Kernels (Python, R, Jupyter Notebooks)

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means

텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)

🔥🌟《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!💪 This repository is ALL You Need!

🍊 📊 💡 Orange: Interactive data analysis

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

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

Machine Learning with the NSL-KDD dataset for Network Intrusion Detection

Earthquake Prediction Challenge with LightGBM and XGBoost

A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4,5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting (GBDT, GBRT, GBM), Random Forest and Adaboost w/categorical features support for Python

Text Classification Algorithms: A Survey

Go Scoring API for PMML

Show how to perform fast retraining with LightGBM in different business cases

Misc Statistics and Machine Learning codes in R

This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.

📒 Experiment tracking tool and model registry

[Data Castle 算法竞赛] 精品旅行服务成单预测 final rank 11

[UNMAINTAINED] Automated machine learning for analytics & production

This is the implementation of Sparse Projection Oblique Randomer Forest

Projects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning