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

Comparing FC VAE / FCN VAE / PCA / UMAP on MNIST / FMNIST

The Predictive Ecosystem Analyzer (PEcAn) is an integrated ecological bioinformatics toolbox.

Efficient similarity search and clustering for Ruby

Examples for Bayesian inference using DynamicHMC.jl and related packages.

Bayesian multi-object tracking

Fast inference for Gaussian processes in problems involving time. Partly built on results from https://proceedings.mlr.press/v161/tebbutt21a.html

Basic Machine Learning implementation with python

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

Bare bone examples of machine learning in TensorFlow

Solve many kinds of least-squares and matrix-recovery problems

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

Matlab interface to Stan, a package for Bayesian inference

Statistical Rethinking course in pymc3

Version 2.1.0 released

C++ template library for probabilistic programming

Exploratory analysis of Bayesian models with Julia

A high-level Bayesian analysis API written in Python

Launch machine learning models into production using flask, docker etc.

Sentiment Analysis & Topic Modeling with Amazon Reviews

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

Bayesian Data Analysis demos for Python

A day to day plan for this challenge. Covers both theoritical and practical aspects

A collection of Bayesian data analysis recipes using PyMC3

Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)

Bayesian Data Analysis demos for R

📜 🎉 Automated reporting of objects in R

Code for Java Deep Learning Cookbook

Survival analysis in health economic evaluation Contains a suite of functions to systematise the workflow involving survival analysis in health economic evaluation. survHE can fit a large range of survival models using both a frequentist approach (by calling the R package flexsurv) and a Bayesian perspective.

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".

rstanarm R package for Bayesian applied regression modeling

A fast approximation to a Dirichlet Process Mixture model (DPM) for clustering genetic data

Code for the paper "Deep Cox Mixtures for Survival Regression", Machine Learning for Healthcare Conference 2021

Full Bayesian Inference for Hidden Markov Models

A simple machine learning framework written in Swift 🤖

Materials of the Nordic Probabilistic AI School 2021.

Pipeline for fast building text classification TF-IDF + LogReg baselines.

Application of the L2HMC algorithm to simulations in lattice QCD.

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

👩🏻‍⚕️Covid-19 estimation and forecast using statistical model; 新型冠状病毒肺炎统计模型预测 (Jan 2020)

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

Gradient based hyperparameter optimization & meta-learning package for TensorFlow

Latent Dirichlet Allocation

MATLAB library for non-negative matrix factorization (NMF): Version 1.8.1

Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall

system performance characterization tool based on linux perf

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.

SecMML: Secure MPC(multi-party computation) Machine Learning Framework

Regression Spline Functions and Classes