553 Open source projects that are alternatives of or similar to VisualML

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

Python code for common Machine Learning Algorithms

经典机器学习算法的极简实现

🏆 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 repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.

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

machine learning algorithm

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

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

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

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

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

simple tutorial on Machine Learning with Scikitlearn

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）

🏭 JavaScript Machine Learning Toolkit

100 Days of ML Coding

Java version of LIBLINEAR

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。

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

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

文本分类基准测试

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

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

Information Retrieval in High Dimensional Data (class deliverables)

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

Matlab library for gradient descent algorithms: Version 1.0.1

A repository for recording the machine learning code

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).

Quick-Data-Science-Experiments

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

Neural network library written in C and Javascript

Autoencoder trained on ImageNet Using Torch 7

This package can be used for dominance analysis or Shapley Value Regression for finding relative importance of predictors on given dataset. This library can be used for key driver analysis or marginal resource allocation models.

Noise removal from images using Convolutional autoencoder

Keras implementation of "A Neural Algorithm of Artistic Style"

Real-time facial expression gathering

dzetsaka : classification plugin for Qgis

R Package: Regularized Principal Component Analysis for Spatial Data

Convolutional AutoEncoder application on MRI images

📊 All of courses, assignments, exercises, mini-projects and books that I've done so far in the process of learning by myself Machine Learning and Data Science.

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

Predicting Google’s stock price using regression

system performance characterization tool based on linux perf

Implementation of G. E. Hinton and R. R. Salakhutdinov's Reducing the Dimensionality of Data with Neural Networks (Tensorflow)

An implementation of "A Neural Algorithm of Artistic Style" in Keras

Used deep reinforcement learning to train a deep neural network to play tic-tac-toe and deployed using tensorflow.js.

Curated Python Notebooks for Data Visualization

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

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

Multi-omics Autoencoder Integration: Deep learning-based heterogenous data analysis toolkit

SESF-Fuse: An Unsupervised Deep Model for Multi-Focus Image Fusion

A new approach to video compression by refining the shortcomings of conventional approach and substituting each traditional component with their neural network counterpart. Our proposed work consists of motion estimation, compression and compensation and residue compression, learned end-to-end to minimize the rate-distortion trade off. The whole…

Label images from Unsplash in browser - using MobileNet on Tensorflow.Js

Large Data Analysis Course Project

Aircraft engine failure prediction model

Implementation of "Disentangled Representation Learning for Non-Parallel Text Style Transfer(ACL 2019)" in Pytorch

Official repository of STYLER: Style Factor Modeling with Rapidity and Robustness via Speech Decomposition for Expressive and Controllable Neural Text to Speech, INTERSPEECH 2021

Estimation and inference from generalized linear models using explicit and implicit methods for bias reduction

A TensorFlow 2.x implementation of Masked Autoencoders Are Scalable Vision Learners