700 Open source projects that are alternatives of or similar to Machine-Learning-Models

machine learning algorithms in Swift

A sparsity aware implementation of "Alternating Direction Method of Multipliers for Non-Negative Matrix Factorization with the Beta-Divergence" (ICASSP 2014).

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.

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.).

A PureScript, browser-based implementation of LDA topic modeling.

A blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.

A SVM model that classifies the reviews as real or fake. Used both the review text and the additional features contained in the data set to build a model that predicted with over 85% accuracy without using any deep learning techniques.

整理记录本人担任课程助教设计的四个机器学习实验，主要涉及简单的线性回归、朴素贝叶斯分类器、支持向量机、CNN做文本分类。内附实验指导书、讲解PPT、参考代码，欢迎各位码友讨论交流。

Artificial intelligence/machine learning course at UCF in Spring 2020 (Fall 2019 and Spring 2019)

Efficient similarity search and clustering for Ruby

An introductory statistics course for social scientists, using Stata

Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.

A Python package to build predictive linear and logistic regression models focused on performance and interpretation

Variational Bayes linear and logistic regression

📈 Regression and Classification with UC Davis student quiz data and exam data

A set of machine learning experiments in Clojure

several methods for text classification

Tracking, notes and programming snippets while learning predictive analytics

Deep Learning From Scratch

Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.

Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.

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

Simple Implementation of Network Intrusion Detection System. KddCup'99 Data set is used for this project. kdd_cup_10_percent is used for training test. correct set is used for test. PCA is used for dimension reduction. SVM and KNN supervised algorithms are the classification algorithms of project. Accuracy : %83.5 For SVM , %80 For KNN

Regression, Scrapers, and Visualization

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

该存储库包含由deeplearning.ai提供的相关课程的个人的笔记和实现代码。

Java version of LIBLINEAR

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)

⚡机器学习实战（Python3）：kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归

Code for Tensorflow Machine Learning Cookbook

🏆 A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.

This repository contains all the programming exercises in Python for the Coursera course called "Machine Learning" by Adjunct Professor Andrew Ng at Stanford University.

TextClf ：基于Pytorch/Sklearn的文本分类框架，包括逻辑回归、SVM、TextCNN、TextRNN、TextRCNN、DRNN、DPCNN、Bert等多种模型，通过简单配置即可完成数据处理、模型训练、测试等过程。

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）

HoG, PCA, PSO, Hard Negative Mining, Sliding Window, Edge Boxes, NMS

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

A document covering machine learning basics. 🤖📊

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

Information Retrieval in High Dimensional Data (class deliverables)

Documents, papers and codes related to Natural Language Processing, including Topic Model, Word Embedding, Named Entity Recognition, Text Classificatin, Text Generation, Text Similarity, Machine Translation)，etc. All codes are implemented intensorflow 2.0.

A curated list of data mining papers about fraud detection.

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

This repo contains regression and classification projects. Examples: development of predictive models for comments on social media websites; building classifiers to predict outcomes in sports competitions; churn analysis; prediction of clicks on online ads; analysis of the opioids crisis and an analysis of retail store expansion strategies using…

gesture recognition toolkit

Machine Learning University: Decision Trees and Ensemble Methods

A curated list of gradient boosting research papers with implementations.

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

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

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

A python library for decision tree visualization and model interpretation.

Jupyter Notebooks and miscellaneous

Large Data Analysis Course Project

bitcoin prediction algorithms

Machine Learning library for the web and Node.

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

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

A sentiment classifier on mixed language (and mixed script) reviews in Tamil, Malayalam and English

A simple implementation of the LOESS algorithm using numpy

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

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。