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

Python code for common Machine Learning Algorithms

经典机器学习算法的极简实现

Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.

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

文本分类基准测试

Quick-Data-Science-Experiments

Starter code of Prof. Andrew Ng's machine learning MOOC in R statistical language

My solution to TUM's Machine Learning MNIST challenge 2016-2017 [winner]

Ruby Scoring API for PMML

simple tutorial on Machine Learning with Scikitlearn

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

(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

Forecast stock prices using machine learning approach. A time series analysis. Employ the Use of Predictive Modeling in Machine Learning to Forecast Stock Return. Approach Used by Hedge Funds to Select Tradeable Stocks

Heart Disease prediction using 5 algorithms

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

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

I will update this repository to learn Machine learning with python with statistics content and materials

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

🏭 JavaScript Machine Learning Toolkit

Data Science algorithms and topics that you must know. (Newly Designed) Recommender Systems, Decision Trees, K-Means, LDA, RFM-Segmentation, XGBoost in Python, R, and Scala.

By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.

Plain python implementations of basic machine learning algorithms

Text Classification Algorithms: A Survey

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

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

Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means

machine learning algorithm

Simple machine learning library / 簡單易用的機器學習套件

텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)

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.

Feature reduction projections and classifier models are learned by training dataset and applied to classify testing dataset. A few approaches of feature reduction have been compared in this paper: principle component analysis (PCA), linear discriminant analysis (LDA) and their kernel methods (KPCA,KLDA). Correspondingly, a few approaches of classification algorithm are implemented: Support Vector Machine (SVM), Gaussian Quadratic Maximum Likelihood and K-nearest neighbors (KNN) and Gaussian Mixture Model(GMM).

Interactive Visual Machine Learning Demos.

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

Matlab library for gradient descent algorithms: Version 1.0.1

100 Days of ML Coding

Building Decision Trees From Scratch In Python

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

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）

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. 🤖📊

bitcoin prediction algorithms

Jupyter Notebooks and miscellaneous

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。

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

📈 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…

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…

Essential NLP & ML, short & fast pure Python code

Machine Learning University: Decision Trees and Ensemble Methods

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.

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.

machine learning algorithms in Swift

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.

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

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

A curated list of gradient boosting research papers with implementations.

gesture recognition toolkit

A curated list of data mining papers about fraud detection.

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