433 Open source projects that are alternatives of or similar to models-by-example

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

Statistical Rethinking course in pymc3

Version 2.1.0 released

사회과학자를 위한 데이터과학 방법론 (코드 저장소)

Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX

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

A collection of Poisson lognormal models for multivariate count data analysis

An implementation of "Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information Networks".

Spline based mesh generation

An R package for large scale estimation with stochastic gradient descent

Gender recognition by voice and speech analysis

This repository will contain all the stuffs required for beginners in ML and DL do follow and star this repo for regular updates

Fake News Detection in Python

Differentiable Gaussian Process implementation for PyTorch

텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)

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

Collection of stats, modeling, and data science tools in Python and R.

Project Page of Combining 3D Morphable Models: A Large scale Face-and-Head Model - [CVPR 2019]

Sentiment analysis on Amazon Review Dataset available at http://snap.stanford.edu/data/web-Amazon.html

COX Proportional risk model and survival analysis implemented by tensorflow.

The "Python Machine Learning (1st edition)" book code repository and info resource

Workshop on tidytranscriptomics: Performing tidy transcriptomics analyses with tidybulk, tidyverse and tidyheatmap

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）

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

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。

Materials of the Nordic Probabilistic AI School 2019.

Fwumious Wabbit, fast on-line machine learning toolkit written in Rust

Testing doing basic regression with web assembly

Hybrid model of Gradient Boosting Trees and Logistic Regression (GBDT+LR) on Spark

machine learning algorithms in Swift

正方验证码识别工具 提供多种方式

Code for Learned Turbo-ype Affine Rank Minimization

An Interactive Approach to Understanding Deep Learning with Keras

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

Machine Learning Procedures and Functions for Neo4j

This repository contains my full work and notes on Coursera's NLP Specialization (Natural Language Processing) taught by the instructor Younes Bensouda Mourri and Łukasz Kaiser offered by deeplearning.ai

🌎 I created this repository for educational purposes. It will host a number of projects as part of the process .

Ytk-learn is a distributed machine learning library which implements most of popular machine learning algorithms(GBDT, GBRT, Mixture Logistic Regression, Gradient Boosting Soft Tree, Factorization Machines, Field-aware Factorization Machines, Logistic Regression, Softmax).

A C++ library of Markov Chain Monte Carlo (MCMC) methods

Java version of LIBLINEAR

A Python package for approximate Bayesian inference and optimization using Gaussian processes

Generalized Analog Regression Downscaling (GARD) code

Combining tree-boosting with Gaussian process and mixed effects models

An example project that predicts risk of credit card default using a Logistic Regression classifier and a 30,000 sample dataset.

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

Implementations of the ICML 2017 paper (with Yarin Gal)

Principal component analysis (PCA) in Ruby

Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model

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

Bayesian Deep Learning: A Survey

Benchmarking and Visualization Toolkit for Penalized Cox Models

Code for the algorithms in the paper: Vaibhav B Sinha, Sukrut Rao, Vineeth N Balasubramanian. Fast Dawid-Skene: A Fast Vote Aggregation Scheme for Sentiment Classification. KDD WISDOM 2018

Multidimensional B-Spline Interpolation of Data on a Regular Grid

arxiv.org/abs/1801.07710v2

Final project of IBM's course https://www.coursera.org/learn/machine-learning-with-python on coursera

Machine Learning models from scratch with a better visualisation

Demo of basic machine learning models in python with Jupter Notebook

Loan Application Data Analysis

📊 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.