6127 Open source projects that are alternatives of or similar to Bnlearn

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

Personal project to compare hierarchical linear regression in PyMC3 and PyStan, as presented at http://pydata.org/london2016/schedule/presentation/30/ video: https://www.youtube.com/watch?v=Jb9eklfbDyg

PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course

Code for "A-NICE-MC: Adversarial Training for MCMC"

Scalable inference for a generative model of astronomical images

Generalized linear mixed-effect model in Python

Variational autoencoders for collaborative filtering

A collection of Bayesian data analysis recipes using PyMC3

Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.

Statistical Rethinking with PyTorch and Pyro

Simulation-based inference in PyTorch

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

Bayesian Data Analysis demos for Python

How to do Bayesian statistical modelling using numpy and PyMC3

PyMC3 educational resources

NIPS 2017: ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching

Fast and Easy Infinite Neural Networks in Python

Statistical Rethinking (2nd Ed) with Tensorflow Probability

Python package for computing the Curie depth from the magnetic anomaly

🎓 Educational application of Hidden Markov Model to Autonomous Driving 🚕🚙🚗

AI Video Processing/Upscaling With VapourSynth in Google Colab

Live training loss plot in Jupyter Notebook for Keras, PyTorch and others

A collection of reference applications using live video analytics capabilities in Azure Media Services

Assignments: CNN for Visual Recognition.

Entry for machine learning

A repo of examples for the matminer (https://github.com/hackingmaterials/matminer) code

TensorFlow 最佳学习资源大全（含课程、书籍、博客、公开课等内容）

Introduction to Probability and Statistics

Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course

This is our solution for WSDM - DiggSci 2020. We implemented a simple yet robust search pipeline which ranked 2nd in the validation set and 4th in the test set. We won the gold prize at innovation track and bronze prize at dataset track.

Doublet detection in single-cell RNA-seq data.

It's my projects

This is a times series anomaly detection algorithm, implemented in Python, for catching multiple anomalies. It uses a moving average with an extreme student deviate (ESD) test to detect anomalous points.

Code repo for the book "Feature Engineering for Machine Learning," by Alice Zheng and Amanda Casari, O'Reilly 2018

Slides produced by Engineers and Data Scientists of Blue Yonder

Solutions in Python for Kevin Murphy's Machine Learning: a Probabilistic Perspective

Baseline of FashionAI Competition based on Keras.

Simple feedforward neural network class written in pure python+numpy

Teal deer (from TL;DR) helps you get the gist of all the stuff you need to read, so you don't have to read it all at once.

Keras implementation of sketch inversion using deep convolution neural networks (synthesising photo-realistic images from pencil sketches)

Código e dados para a matéria "O que 15 mil tweets revelam sobre seu candidato" || Code and data for the story "What 15k tweets show about your candidate"

demos for PyBay talk: Using Randomness to make code faster

SalmonTE is an ultra-Fast and Scalable Quantification Pipeline of Transpose Element (TE) Abundances

Verify Estonian e-id signatures on Ethereum

Códigos explicados nos vídeos do canal Universo Discreto (YouTube)

Russian SuperGLUE benchmark

Topic modeling with BigARTM: an interactive book

Code to analyse structural covariance brain networks using python.

Machine Learning for Economics

Code and Notebooks for Spark Tutorials for Learning Journal @ Youtube

A generative network for animal vocalizations. For dimensionality reduction, sequencing, clustering, corpus-building, and generating novel 'stimulus spaces'. All with notebook examples using freely available datasets.

Used LSTM Network to classify eeg signals based on stimuli the subject recieved (visual or audio)

Anonymization methods for network security.

Binary Convolution Network for faster real-time processing in ASICs

Adventure into using multi attention recurrent neural networks for time-series (city traffic) for the 2017-11-18 McKinsey IronMan (24h non-stop) prediction challenge

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