6744 Open source projects that are alternatives of or similar to Bayesian Neural Networks

GPstuff - Gaussian process models for Bayesian analysis

R package to interface with OpenML

دوره 12 ساعته یادگیری عمیق با چارچوب Keras

Statistical Rethinking (2nd Ed) with Tensorflow Probability

This repository consists of all my Machine Learning Projects.

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara

Code for Tensorflow Machine Learning Cookbook

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

A Julia machine learning framework

Succinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning.

IPython widgets, interactive plots, interactive machine learning

Comparison tools

Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code

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

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

An Interactive Approach to Understanding Deep Learning with Keras

An open-source, low-code machine learning library in Python

My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge.

Boltzmann Machines in TensorFlow with examples

Scalable inference for a generative model of astronomical images

Collection of probabilistic models and inference algorithms

Bayesian Data Analysis demos for Python

Natural Gradient, Variational Inference

Probabilistic question-asking system: the program asks, the users answer. The minimal goal of the program is to identify what the user needs (a target), even if the user is not aware of the existence of such a thing/product/service.

In this project I aim to apply Various Predictive Maintenance Techniques to accurately predict the impending failure of an aircraft turbofan engine.

An implementation of multivariate projection pursuit regression and univariate classification

InstantDL: An easy and convenient deep learning pipeline for image segmentation and classification

A collection of Methods and Models for various architectures of Artificial Neural Networks

Sequential Monte Carlo algorithm for approximation of posterior distributions.

Material for a workshop on Bayesian stats with R

CmdStanR: the R interface to CmdStan

Python/R library for feature selection in neural nets. ("Feature selection using Stochastic Gates", ICML 2020)

Online machine learning methods

tiny fast portable real-time deep neural network for regression and classification within 50 LOC.

D-Lab's 6 hour introduction to machine learning in Python. Learn how to perform classification, regression, clustering, and do model selection using scikit-learn and TPOT.

Python Machine Learning Algorithms

Open-source project hosted at https://makeuseofdata.com to crowdsource a robust collection of notes related to data science (math, visualization, modeling, etc)

Various methods for generating synthetic data for data science and ML

Efficient, lightweight variational inference and approximation bounds

Minimalistic Multiple Layer Neural Network from Scratch in Python.

Full Bayesian Inference for Hidden Markov Models

Automatic Reparameterisation of Probabilistic Programs

Generative Models Tutorial with Demo: Bayesian Classifier Sampling, Variational Auto Encoder (VAE), Generative Adversial Networks (GANs), Popular GANs Architectures, Auto-Regressive Models, Important Generative Model Papers, Courses, etc..

All Algorithms implemented in R

Artificial Neural Network

Curated Tensorflow code resources to help you get started with Deep Learning.

BAS R package https://merliseclyde.github.io/BAS/

Makes Interactive Chart Widget, Cleans raw data, Runs baseline models, Interactive hyperparameter tuning & tracking

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

天池医疗AI大赛[第一季]：肺部结节智能诊断 UNet/VGG/Inception/ResNet/DenseNet

BERT-NER (nert-bert) with google bert https://github.com/google-research.

Bayesian Data Analysis demos for R

Variational autoencoders for collaborative filtering

Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning

A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.

Github repo with tutorials to fine tune transformers for diff NLP tasks

Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学

food image to recipe with deep convolutional neural networks.

A collection of Bayesian data analysis recipes using PyMC3