Popular GitHub Repositories for Bayes

100 Days of ML Coding

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

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

Text Classification Algorithms: A Survey

Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.

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

Diffusion Classifier leverages pretrained diffusion models to perform zero-shot classification without additional training

??《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!? This repository is ALL You Need!

Learning to create Machine Learning Algorithms

Artificial intelligence/machine learning data structures and Swift algorithms for future iOS development. bayes theorem, neural networks, and more AI.

Tensorflow Implementation of Knowledge-Guided CVAE for dialog generation ACL 2017. It is released by Tiancheng Zhao (Tony) from Dialog Research Center, LTI, CMU

A repository contains more than 12 common statistical machine learning algorithm implementations. 常见10余种机器学习算法原理与实现及视频讲解。@月来客栈 出品

Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.

OpenTextClassification is all you need for text classification! Open text classification for everyone, enjoy your NLP journey! 这可能是目前为止最全面的开源文本分类项目，支持中英双语、多种模型、多种任务。

This repository explores the variety of techniques and algorithms commonly used in machine learning and the implementation in MATLAB and PYTHON.

中文文本分类实践，基于搜狗新闻语料库，采用传统机器学习方法以及预训练模型等方法

This is a collection of some of the important machine learning algorithms which are implemented with out using any libraries. Libraries such as numpy and pandas are used to improve computational complexity of algorithms

Implementing Bayes by Backprop with PyTorch. Applied on time-series prediction.

Sentiment analysis with Machine Learning