1004 Open source projects that are alternatives of or similar to handson-ml

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

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

文本分类基准测试

Source code of the model used in Tensorflow Speech Recognition Challenge (https://www.kaggle.com/c/tensorflow-speech-recognition-challenge). The solution ranked in top 5% in private leaderboard.

Building Decision Trees From Scratch In Python

A python library for decision tree visualization and model interpretation.

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

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)

A curated list of gradient boosting research papers with implementations.

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

[UNMAINTAINED] Automated machine learning for analytics & production

In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.

🌳 Stacked Gradient Boosting Machines

Stacked Generalization (Ensemble Learning)

Machine Learning University: Decision Trees and Ensemble Methods

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

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

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

Repository for the AdaptiveRandomForest algorithm implemented in MOA 2016-04

Python code for common Machine Learning Algorithms

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

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.

Machine Learning library for the web and Node.

Aircraft engine failure prediction model

Automatic machine learning for tabular data. ⚡🔥⚡

Interactive SVM Explorer, using Dash and scikit-learn

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

🏭 JavaScript Machine Learning Toolkit

This is the official implementation for the paper 'Deep forest: Towards an alternative to deep neural networks'

(BOW, TF-IDF, Word2Vec, BERT) Word Embeddings + (SVM, Naive Bayes, Decision Tree, Random Forest) Base Classifiers + Pre-trained BERT on Tensorflow Hub + 1-D CNN and Bi-Directional LSTM on IMDB Movie Reviews Dataset

Solution of the Titanic Kaggle competition

Predicting the winner of 2019 cricket world cup using random forest algorithm

simple tutorial on Machine Learning with Scikitlearn

Machine learning for C# .Net

bitcoin prediction algorithms

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

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

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

Machine Learning inference engine for Microcontrollers and Embedded devices

A document covering machine learning basics. 🤖📊

A curated list of data mining papers about fraud detection.

🍊 📊 💡 Orange: Interactive data analysis

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.).

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

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

텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)

中文文本分类实践，基于搜狗新闻语料库，采用传统机器学习方法以及预训练模型等方法

Using LSTM network for time series forecasting

InfiniteBoost: building infinite ensembles with gradient descent

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

Formed trajectories of sets of points.Experimented on finding similarities between trajectories based on DTW (Dynamic Time Warping) and LCSS (Longest Common SubSequence) algorithms.Modeled trajectories as strings based on a Grid representation.Benchmarked KNN, Random Forest, Logistic Regression classification algorithms to classify efficiently t…

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

基于scikit-learn实现对新浪新闻的文本分类，数据集为100w篇文档，总计10类，测试集与训练集1:1划分。分类算法采用SVM和Bayes，其中Bayes作为baseline。

Class-imbalanced / Long-tailed ensemble learning in Python. Modular, flexible, and extensible. | 模块化、灵活、易扩展的类别不平衡/长尾机器学习库

python library implementing ensemble methods for regression, classification and visualisation tools including Voronoi tesselations.

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).

Pytorch、Scikit-learn实现多种分类方法，包括逻辑回归（Logistic Regression）、多层感知机（MLP）、支持向量机（SVM）、K近邻（KNN）、CNN、RNN，极简代码适合新手小白入门，附英文实验报告（ACM模板）

Training SVM classifier to recognize people expressions (emotions) on Fer2013 dataset

Text Classification Algorithms: A Survey

⏱ Benchmarks of machine learning inference for Go