There are 8 repositories under bayes topic.
Curated list of Python resources for data science.
Text and code for the forthcoming second edition of Think Bayes, by Allen Downey.
Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.
A Naive Bayes machine learning implementation in Elixir.
情感分析、文本分类、词典、bayes、sentiment analysis、TextCNN、classification、tensorflow、BERT、CNN、text classification
Python code snippets from Discrete Mathematics for Computer Science specialization at Coursera
NaiveBayes classifier for JavaScript
商品类目预测,使用 Spring Boot 开发框架和 Spark MLlib 机器学习框架,通过 TF-IDF 和 Bayes 算法,训练出一个商品类目预测模型。该模型可以根据商品名称自动预测出商品类目。项目对外提供 RESTFul 接口。
General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics
Detecting Autism Spectrum Disorder in Children With Computer Vision - Adapting facial recognition models to detect Autism Spectrum Disorder
Clique recycling non-Gaussian (multi-modal) factor graph solver; also see Caesar.jl.
Using Computer with your Statistics Major Course
📈📄👀A lookup repo for a variety of discrete and continuous distributions (incl. Beta, Binomial, Cauchy, Chi-squared, Geometric, Hypergeometric, Normal & Poisson)
Gauss Naive Bayes in Python From Scratch.
Bayesian entropy estimation in Python - via the Nemenman-Schafee-Bialek algorithm
A small, no dependencies, Naive Bayes Text Classifier for JavaScript
📚 The Bayes Way 🎓
Demonstration of using Naive Bayes to predict user inputs with Kotlin 1.2 std-lib
Slides and code for the Stable Isotope Mixing Models course given by Andrew Parnell and Andrew Jackson
Bayesian inference from binary causal models
Autoregressive Bayesian linear model
Underlying code for the online stats training website.
Intention Mining in Social Networking. It Mines Emotions and polarity for the given keyword . For the keyword it searchers the twitter for the comments and analyzes the results for various events such as Election results, Sports prediction Movie ratings, Breaking news events such as demonetisation and many more. Bayes , Maximum Entropy and Hidden Markov models are used to analyse the results. It requires R shiny package installed.