1465 Open source projects that are alternatives of or similar to Chefboost

This is a comprehensive ML techniques with python: Define the Problem- Specify Inputs & Outputs- Data Collection- Exploratory data analysis -Data Preprocessing- Model Design- Training- Evaluation

Go Scoring API for PMML

Solution of the Titanic Kaggle competition

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

A super-fast and scalable Random Forest library based on fast histogram decision tree algorithm and distributed bagging framework. It can be used for binary classification, multi-label classification, and regression tasks. This library provides both Python and command line interface to users.

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

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

Repository for the AdaptiveRandomForest algorithm implemented in MOA 2016-04

A scalable python-based framework for gene regulatory network inference using tree-based ensemble regressors.

Python code for common Machine Learning Algorithms

Universal Reddit Scraper - A comprehensive Reddit scraping command-line tool written in Python.

Machine learning for C# .Net

Machine Learning algorithms coded from scratch

Kaggle Kernel for House Prices competition https://www.kaggle.com/massquantity/all-you-need-is-pca-lb-0-11421-top-4

[UNMAINTAINED] Automated machine learning for analytics & production

👨🏽‍🏫You can learn about what data science is and why it's important in today's modern world. Are you interested in data science?🔋

A library of extension and helper modules for Python's data analysis and machine learning libraries.

Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one written in C++, along with various language-specific wrappers.

Public repository for the PM4Py (Process Mining for Python) project.

useR! 2016 Tutorial: Machine Learning Algorithmic Deep Dive http://user2016.org/tutorials/10.html

A unified framework for machine learning with time series

H2O.ai Machine Learning Interpretability Resources

人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

(AAAI' 20) A Python Toolbox for Machine Learning Model Combination

Practical Data Science with Ruby based tools.

Companion code for the book "Mastering Social Media Mining with Python"

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

ELKI Data Mining Toolkit

深度学习在推荐系统中的应用及论文小结。

🌳 Stacked Gradient Boosting Machines

Codes and dashboards for 4th place solution for Kaggle's Home Credit Default Risk competition

model-describer : Making machine learning interpretable to humans

Introduction to Data Science

A collection of notebooks of my Machine Learning class written in python 3

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

Code for the paper "BIOLITMAP: a web-based geolocated and temporal visualization of the evolution of bioinformatics publications" in Oxford Bioinformatics.

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Python Data Science and Machine Learning Library for the Ethereum and ERC-20 Blockchain

📢 Ready to learn or review your knowledge!

Multi-class confusion matrix library in Python

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)

MLBox is a powerful Automated Machine Learning python library.

Dex : The Data Explorer -- A data visualization tool written in Java/Groovy/JavaFX capable of powerful ETL and publishing web visualizations.

pyclustring is a Python, C++ data mining library.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.

Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning

A python library for decision tree visualization and model interpretation.

📝 Подборка ресурсов по машинному обучению

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

General Assembly's 2015 Data Science course in Washington, DC

An efficient Python implementation of the Apriori algorithm.

Text Classification Algorithms: A Survey

YouTube Like Count Predictions using Machine Learning

The Accelerator is a tool for fast and reproducible processing of large amounts of data.

A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms, accessible to everyone.

Heart Disease prediction using 5 algorithms

Misc Statistics and Machine Learning codes in R

IPython Cookbook, Second Edition, by Cyrille Rossant, Packt Publishing 2018

A community run, 5-day PyTorch Deep Learning Bootcamp