322 Open source projects that are alternatives of or similar to AIML-Projects

Python package for combining diarization system outputs.

Building Decision Trees From Scratch In Python

YouTube Like Count Predictions using Machine Learning

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.

Go Scoring API for PMML

R package "missRanger" for fast imputation of missing values by random forests.

Reproduce research from paper "Predicting the direction of stock market prices using random forest"

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

exploratory data analysis using random forests

Machine Learning inference engine for Microcontrollers and Embedded devices

In this work, we propose a deterministic version of Local Interpretable Model Agnostic Explanations (LIME) and the experimental results on three different medical datasets shows the superiority for Deterministic Local Interpretable Model-Agnostic Explanations (DLIME).

This repository contains an example of each of the Ensemble Learning methods: Stacking, Blending, and Voting. The examples for Stacking and Blending were made from scratch, the example for Voting was using the scikit-learn utility.

An Efficient, Scalable and Optimized Python Framework for Deep Forest (2021.2.1)

Receipt.ID is a multi-label, multi-class, hierarchical classification system implemented in a two layer feed forward network.

Using Tensorflow and a Support Vector Machine to Create an Image Classifications Engine

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

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.).

Jupyter Notebooks and miscellaneous

Scripts, tools and example data for mapping wetland ecosystems using data driven R statistical methods like Random Forests and open source GIS

An end-to-end machine learning and data mining framework on Hadoop

Handwritten Digit Recognition using Machine Learning and Deep Learning

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

ML-powered Loan-Marketer Customer Filtering Engine

Using LSTM network for time series forecasting

A random forest

利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码

Machine Learning library written in Python and NumPy.

A curated list of gradient boosting research papers with implementations.

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

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.

ThunderGBM: Fast GBDTs and Random Forests on GPUs

Machine Learning algorithms coded from scratch

随机森林，Random Forest（RF）

Generalized Random Forests

Conformalized Quantile Regression

A New, Interactive Approach to Learning Data Science

Machine learning for C# .Net

深度学习面试宝典（含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向）

InfiniteBoost: building infinite ensembles with gradient descent

This is the official implementation for the paper 'AutoEncoder by Forest'

Machine Learning library for the web and Node.

ML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xgboost in Python

This repository contains some datasets that I have collected in Recommender Systems.

Python implementation of Andrew Ng's ML course projects

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

Applying Data Science and Machine Learning to Solve Real World Business Problems

🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams

Book recommender system using collaborative filtering based on Spark

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

AI-related tutorials. Access any of them for free → https://towardsai.net/editorial

Source code of CHAMELEON - A Deep Learning Meta-Architecture for News Recommender Systems

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

A django app that builds item-based suggestions for users.

A python library for decision tree visualization and model interpretation.

A list of interesting graph neural networks (GNN) links with a primary interest in recommendations and tensorflow that is continually updated and refined

Graph Neural Network

Classifies genes as an oncogene, tumor suppressor gene, or as a non-driver gene by using Random Forests

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

Vídeos e códigos do Universo Discreto ensinando o fundamental de Machine Learning em Python. Para mais detalhes, acompanhar a playlist listada.

Compatibility Family Learning for Item Recommendation and Generation