28 Repositories

### Python naive-bayes Libraries

##### Repository for "Improving evidential deep learning via multi-task learning," published in AAAI2022

Improving evidential deep learning via multi task learning It is a repository of AAAI2022 paper, “Improving evidential deep learning via multi-task le

##### The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training

[ICLR 2022] The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training The Unreasonable Effectiveness of

##### Cairo-bloom - A naive bloom filter implementation in Cairo

🥀 cairo-bloom A naive bloom filter implementation in Cairo. A Bloom filter is a

##### Object classification with basic computer vision techniques

naive-image-classification Object classification with basic computer vision techniques. Final assignment for the computer vision course I took at univ

##### Sentiment Classification using WSD, Maximum Entropy & Naive Bayes Classifiers

Sentiment Classification using WSD, Maximum Entropy & Naive Bayes Classifiers

##### Implementation of ML models like Decision tree, Naive Bayes, Logistic Regression and many other

ML_Model_implementaion Implementation of ML models like Decision tree, Naive Bayes, Logistic Regression and many other dectree_model: Implementation o

##### Bayesian A/B testing

bayesian_testing is a small package for a quick evaluation of A/B (or A/B/C/...) tests using Bayesian approach.

##### Python Machine Learning Jupyter Notebooks (ML website)

Python Machine Learning Jupyter Notebooks (ML website) Dr. Tirthajyoti Sarkar, Fremont, California (Please feel free to connect on LinkedIn here) Also

##### Clustering with variational Bayes and population Monte Carlo

pypmc pypmc is a python package focusing on adaptive importance sampling. It can be used for integration and sampling from a user-defined target densi

##### General Assembly's 2015 Data Science course in Washington, DC

DAT8 Course Repository Course materials for General Assembly's Data Science course in Washington, DC (8/18/15 - 10/29/15). Instructor: Kevin Markham (

##### Text and code for the forthcoming second edition of Think Bayes, by Allen Downey.

Think Bayes 2 by Allen B. Downey The HTML version of this book is here. Think Bayes is an introduction to Bayesian statistics using computational meth

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

Bayesian Neural Networks Pytorch implementations for the following approximate inference methods: Bayes by Backprop Bayes by Backprop + Local Reparame

##### Automatic library of congress classification, using word embeddings from book titles and synopses.

Automatic Library of Congress Classification The Library of Congress Classification (LCC) is a comprehensive classification system that was first deve

##### Indonesia's negative news detection using gaussian naive bayes with Django+Scikir Learn

Introduction Indonesia's negative news detection using gaussian naive bayes build with Django and Scikit Learn. There is also any features, are: Input

##### SymPy-powered, Wolfram|Alpha-like answer engine totally in your browser, without backend computation

SymPy Beta SymPy Beta is a fork of SymPy Gamma. The purpose of this project is to run a SymPy-powered, Wolfram|Alpha-like answer engine totally in you

##### Predict Breast Cancer Wisconsin (Diagnostic) using Naive Bayes

Naive-Bayes Predict Breast Cancer Wisconsin (Diagnostic) using Naive Bayes Downloading Data Set Use our Breast Cancer Wisconsin Data Set Also you can

##### Understanding the Properties of Minimum Bayes Risk Decoding in Neural Machine Translation.

Understanding Minimum Bayes Risk Decoding This repo provides code and documentation for the following paper: Müller and Sennrich (2021): Understanding

##### A naive Bayes model for cancer classification using a set of documents

Naivebayes text classifcation model for cancer and noncancer documents Author: Alex King Purpose Requirements/files included How to use 1. Purpose The

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

Bayes-Newton Bayes-Newton is a library for approximate inference in Gaussian processes (GPs) in JAX (with objax), built and actively maintained by Wil

##### Code accompanying the paper "How Tight Can PAC-Bayes be in the Small Data Regime?"

How Tight Can PAC-Bayes be in the Small Data Regime? This is the code to reproduce all experiments for the following paper: @inproceedings{Foong:2021:

##### Code implementation for the paper 'Conditional Gaussian PAC-Bayes'.

CondGauss This repository contains PyTorch code for the paper Stochastic Gaussian PAC-Bayes. A novel PAC-Bayesian training method is implemented. Ther

##### A naive ROS interface for visualDet3D.

YOLO3D ROS Node This repo contains a Monocular 3D detection Ros node. Base on https://github.com/Owen-Liuyuxuan/visualDet3D All parameters are exposed

##### Module is created to build a spam filter using Python and the multinomial Naive Bayes algorithm.

Naive-Bayes Spam Classificator Module is created to build a spam filter using Python and the multinomial Naive Bayes algorithm. Main goal is to code a

##### Trying to replicate (albeit unsuccessfully) the phenomenon of boids using Ursina in a naive manner.

Boids_Boi Trying to replicate (albeit unsuccessfully) the phenomenon of boids using Ursina in a naive manner. Please install the Ursina module before

##### 30 Days Of Machine Learning Using Pytorch

Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

##### The (extremely) naive sentiment classification function based on NBSVM trained on wisesight_sentiment

thai_sentiment The naive sentiment classification function based on NBSVM trained on wisesight_sentiment วิธีติดตั้ง pip install thai_sentiment==0.1.3

##### Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

30 Days Of Machine Learning Using Pytorch Objective of the repository is to learn and build machine learning models using Pytorch. List of Algorithms

##### 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.

H2O H2O is an in-memory platform for distributed, scalable machine learning. H2O uses familiar interfaces like R, Python, Scala, Java, JSON and the Fl