1044 Open source projects that are alternatives of or similar to ml

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

⚡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

Implementations of machine learning algorithm by Python 3

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

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

Python code for common Machine Learning Algorithms

Quick-Data-Science-Experiments

Interactive Visual Machine Learning Demos.

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.

machine learning algorithm

simple tutorial on Machine Learning with Scikitlearn

My solutions for Assignments of CS231n: Convolutional Neural Networks for Visual Recognition

machine learning algorithms in Swift

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

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

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).

Animated Visualizations of Popular Machine Learning 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

🏆 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.

Essential NLP & ML, short & fast pure Python code

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

Plain python implementations of basic machine learning algorithms

机器学习教程，本教程包含基于numpy、sklearn与tensorflow机器学习，也会包含利用spark、flink加快模型训练等用法。本着能够较全的引导读者入门机器学习。

Java version of LIBLINEAR

文本分类基准测试

🏭 JavaScript Machine Learning Toolkit

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

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

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。

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.

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）

100 Days of ML Coding

numpy 实现的 周志华《机器学习》书中的算法及其他一些传统机器学习算法

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

텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)

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

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

文本聚类（Kmeans、DBSCAN、LDA、Single-pass）

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

Building Decision Trees From Scratch 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…

Efficient similarity search and clustering for Ruby

Matlab library for gradient descent algorithms: Version 1.0.1

A document covering machine learning basics. 🤖📊

FUKinect-Fall dataset was created using Kinect V1. The dataset includes walking, bending, sitting, squatting, lying and falling actions performed by 21 subjects between 19-72 years of age.

OCR Machine Learning in python

Using machine learning on your anki collection to enhance the scheduling via semantic clustering and semantic similarity

Gaussian mixture models, k-means, mini-batch-kmeans and k-medoids clustering

Large Data Analysis Course Project

Ruby Scoring API for PMML

Information Retrieval in High Dimensional Data (class deliverables)

Python Clustering Algorithms

In this repository, You can find the files which implement dimensionality reduction on the hyperspectral image(Indian Pines) with classification.

zAnalysis是基于Pascal语言编写的大型统计学开源库

(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

Migrated to: https://gitlab.com/Oslandia/osm-data-classification

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.

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

Heart Disease prediction using 5 algorithms

Sentiment Analysis & Topic Modeling with Amazon Reviews