Test symmetries with sklearn decision tree models
Setup
Begin from an environment with a recent version of python 3.
source setup.sh
Leave the environment with deactivate
. Clean up fully by removing env/
.
Run examples
make
Begin from an environment with a recent version of python 3.
source setup.sh
Leave the environment with deactivate
. Clean up fully by removing env/
.
make
Highly interpretable, sklearn-compatible classifier based on decision rules This is a scikit-learn compatible wrapper for the Bayesian Rule List class
Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree
Data Efficient Decision Making
MBTR is a python package for multivariate boosted tree regressors trained in parameter space.
implementation of machine learning Algorithms such as decision tree and random forest and xgboost on darasets then compare results for each and implement ant colony and genetic algorithms on tsp map, play blackjack game and robot in grid world and evaluate reward for it
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
pyGAM Generalized Additive Models in Python. Documentation Official pyGAM Documentation: Read the Docs Building interpretable models with Generalized
Time series analysis today is an important cornerstone of quantitative science in many disciplines, including natural and life sciences as well as eco
Auto_TS: Auto_TimeSeries Automatically build multiple Time Series models using a Single Line of Code. Now updated with Dask. Auto_timeseries is a comp
First version to go on Zenodo 🤖 second major version ♊
Source code(tar.gz)English | 简体中文 AutoX是什么? AutoX一个高效的自动化机器学习工具,它主要针对于表格类型的数据挖掘竞赛。 它的特点包括: 效果出色: AutoX在多个kaggle数据集上,效果显著优于其他解决方案(见效果对比)。 简单易用: AutoX的接口和sklearn类似,方便上手使用。
ml4ir: Machine Learning for Information Retrieval | changelog Quickstart → ml4ir Read the Docs | ml4ir pypi | python ReadMe ml4ir is an open source li
pure-predict speeds up and slims down machine learning prediction applications. It is a foundational tool for serverless inference or small batch prediction with popular machine learning frameworks l
Using PySpark we can process data from Hadoop HDFS, AWS S3, and many file systems. PySpark also is used to process real-time data using Streaming and
This project is made to help you scale from a basic Machine Learning project for research purposes to a production grade Machine Learning web service
SDK: Overview of the Kubeflow pipelines service Kubeflow is a machine learning (ML) toolkit that is dedicated to making deployments of ML workflows on
Customer Segmentation with RFM Scores and K-means RFM Segmentation table: K-Means Clustering: Business Problem Rule-based customer segmentation machin
2021 Machine Learning Security Evasion Competition This repository contains code samples for the 2021 Machine Learning Security Evasion Competition. P
Jina is geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the effici
sk-dist: Distributed scikit-learn meta-estimators in PySpark What is it? sk-dist is a Python package for machine learning built on top of scikit-learn
Trading Tesla with Machine Learning and Sentiment Analysis An interactive program to train a Random Forest Classifier to predict Tesla daily prices us
An open-source, low-code machine learning library in Python 🚀 Version 2.3.5 out now! Check out the release notes here. Official • Docs • Install • Tu
geneticml This package contains a simple and lightweight genetic algorithm for optimization of any machine learning model. Installation Use pip to ins
Linear regression for data with measurement errors and intrinsic scatter (BCES) Python module for performing robust linear regression on (X,Y) data po
Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets Datasets Used: Iris dataset,
[Book-2021] Practical MLOps O'Reilly Book
CML with cloud compute This repository contains a sample project using CML with Terraform (via the cml-runner function) to launch an AWS EC2 instance
Auto-ML tool specialized in detecting of outliers Description This tool will allows you, with a Dash visualization, to compare 10 models of machine le
Evidently helps analyze machine learning models during validation or production monitoring. The tool generates interactive visual reports and JSON profiles from pandas DataFrame or csv files. Current
sklearn-evaluation Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking, and Jupyter notebook analysis. Suppo